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- ##[[Signal Energy and Power_(ECE301Summer2008asan)|Signal Energy and Power]] ##[[Continuous-Time and Discrete-Time_(ECE301Summer2008asan)|Continuous-Time and Discrete-Time]]7 KB (921 words) - 06:08, 21 October 2011
- (a) The FT of <math>X(j\omega)</math> of a continuous-time signal x(t) is periodic (b) The FT of <math>X(e^{j\omega})</math> of a continuous-time signal x[n] is periodic4 KB (777 words) - 11:49, 21 November 2008
- .../math> of the signal x[n] is also periodic with period N. For the periodic signal x[n], find the values of <math>a_0,a_1,...,a_{N-1}.</math> Express your an 1)b)Evaluate the value of <math>(1/N)*\sum_{n=<N>}|x[n]|^2</math> for the signal x[n] given in part (a).4 KB (815 words) - 10:57, 21 November 2008
- The command is ifft. It takes in a vector representing your signal and produces a vector of the fourier series coefficients. Two examples are The signal is represented by the graph below and is periodic for all time:5 KB (834 words) - 17:26, 23 April 2013
- ...he Fourier Transform.... In particular, Fourier reasoned that an aperiodic signal can be viewed as a periodic singal with an infinite period." An example of ...nd the sound of the musical chord represented by these notes (the function/signal itself).3 KB (431 words) - 17:29, 23 April 2013
- ...ecause it does not specify from what the signal is being recreated. If the signal is for example not band-limited, it cannot be reconstructed at all. ...an the Nyquist rate in rare cases you are able to properly reconstruct the signal.4 KB (689 words) - 12:48, 12 December 2008
- [[Category:signal processing]] 2) Digital Signal = a signal that can be represented by a sequence of 0's and 1's.3 KB (532 words) - 06:43, 16 September 2013
- *<math>\omega_m</math>: Maximum frequency in a band-limited signal (<math> = max(\{|w|\ :\ w \neq 0\})</math> ...hen the band-limited signal can be uniquely reconstructed from the sampled signal.2 KB (406 words) - 11:08, 12 November 2010
- [[Category:signal processing]] <li>Signal Characteristics</li>3 KB (508 words) - 06:43, 16 September 2013
- [[Category:signal processing]] <strong>Continuous-time:</strong> (a.k.a. Dirac delta function)<br/>2 KB (408 words) - 06:43, 16 September 2013
- == Continuous-time domain == *[[CT Time-averaged Power of a Signal over an infinite interval_ECE301Fall2008mboutin]] {{:CT Power of a Signal_8 KB (989 words) - 07:20, 5 February 2009
- ...Fourier transform of x[n], which is the sampled signal of continuous time signal x(t) <br>546 B (93 words) - 20:27, 18 February 2009
- [[Category:signal processing]]769 B (105 words) - 06:44, 16 September 2013
- [[Category:signal processing]]2 KB (324 words) - 06:45, 16 September 2013
- Note: PM refers to the official course book, Digital Signal Processing, 3rd edition, J.G. Proakis and D.G. Manolakis. ...due.edu/~bouman/ece438/lecture/module_1/1.1_signals/1.1.1_signal_types.pdf Signal Types]8 KB (1,226 words) - 11:40, 1 May 2009
- == Continuous Signal == Continuous signal is a signal that varies with time, and can be represented as a function of time, x(t).2 KB (311 words) - 16:27, 3 December 2008
- == Periodic Signal == Notice, the signal is the same throughout each cycle.481 B (60 words) - 07:15, 14 April 2010
- A discrete time signal is periodic if there exists T > 0 such that x(t + T) = x(t) A continuous time signal is periodic if there exists some integer N > 0 such that x[n + N] = x[n]1 KB (205 words) - 07:20, 14 April 2010
- A continuous time signal is periodic if there exists a value <math> T </math> such that <math> x(t + A discrete time signal is periodic if there exists a value <math> N </math> such that <math> X[n +1 KB (169 words) - 07:22, 14 April 2010
- A continuous time signal x(t) is periodic if there exists T such that x(t + T) = x(t) for all t. <br A discrete time signal x[n] is periodic if there exists some integer N such that x[n + N] = x[n] f1 KB (192 words) - 07:28, 14 April 2010
- A Continuous Time signal is said to be periodic if there exists <math>\ T > 0</math> such that <math A Discrete Time signal is said to be periodic if there exists <math>\ N > 0</math> (where N is an1 KB (221 words) - 12:21, 5 September 2008
- == Periodic Signal Definition == *For a Continuous-time signal1 KB (209 words) - 09:49, 5 September 2008
- For a continuous-time signal <br> ...m_{T \to \infty} {\frac{E(\infty)}{2T}} = 0 ................ Finite-energy Signal</math><br>647 B (89 words) - 21:00, 4 September 2008
- Computation of Signal Energy and power. Source for definition Of Continuous Signal: Wikipedia.778 B (99 words) - 13:21, 5 September 2008
- == For a Continuous Time Signal==788 B (127 words) - 12:34, 5 September 2008
- A periodic signal is one that for a given real number "a": ===Periodic Signal===1 KB (195 words) - 07:20, 14 April 2010
- A signal is periodic if there exists some T>0 such that: A signal is NOT periodic if the converse is true, there DOESN'T exists some T>0 such688 B (106 words) - 07:08, 14 April 2010
- ==Periodic Signal== A continuous time (CT) signal is periodic if it there exists some T such that x(t+T)=x(t) for all t.811 B (148 words) - 13:12, 5 September 2008
- ==Periodic Signal== to prove a CT signal is continuous we must prove that there exists a value T such that x(t) = x(388 B (84 words) - 13:37, 5 September 2008
- '''Changing a Periodic Continuous Time Signal to a Non-Periodic Discrete Time Signal''' ...nsider the continuous time signal <math>x(t)=sin(t)</math>. Plotting this signal yields a smooth waveform that repeats itself with period <math>T=2\pi</math3 KB (536 words) - 11:07, 10 September 2008
- == Continuous to discrete time signal== I used the signal <math>y = cos(n)\,</math> as the signal of my graph1 KB (196 words) - 20:31, 10 September 2008
- === Periodic Continuous Time Signal === ...y people used in Homework 1 for their example of a periodic function. The signal repeats itself at intervals of <math> 2\pi </math>.1 KB (196 words) - 11:07, 10 September 2008
- == CT periodic signal == An example of a periodic signal in continuous time is:1 KB (227 words) - 17:24, 10 September 2008
- I chose to use the CT (continuous time)periodic signal: y(t) = cos(t). The signal can be expressed as both periodic and non-periodic in DT (discrete time).809 B (142 words) - 17:35, 10 September 2008
- A system is called time invariant if for any input signal x(t)(x[n]) and for any t0 belongs to R, the response to the shifted inputX( ...= 10 x(t-t0)where as a system is called time variant when we find an input signal for which the condition of time invariance is violated.2 KB (379 words) - 18:38, 10 September 2008
- ...ework 1 were boring (including mine) so I thought I'd broaden the periodic signal pool. I chose the CT signal: <math>x(t) = |2*cos(.5*t)|</math> . A graph of this signal in continuous time is shown below.1 KB (207 words) - 17:25, 11 September 2008
- <b>Changing a Periodic Continuous Time Signal to a Non-Periodic Discrete Time Signal</b> The signal I chose for this part can be found [[HW1.4 Wei Jian Chan - Periodic and Non1 KB (186 words) - 16:07, 11 September 2008
- 1.This is a sine function of period 2. Function is sin(pi*t). Continuous Signal. 2. '''Periodic DT Signal'''This is the discrete signal of the same function in 1 with sampling time of 0.075. I got the diagram on642 B (86 words) - 10:23, 12 September 2008
- A system is called "'''time invariant'''" if for any input signal x(t) in continuous time or x[n] in discrete time and for any time <math>t_0 A system is called "'''time variant'''" if for any input signal x(t) in continuous time or x[n] in discrete time and for any time <math>t_01 KB (193 words) - 18:59, 18 September 2008
- == Example of Computation of Fourier series of a CT SIGNAL == ==The Signal==2 KB (384 words) - 10:56, 16 September 2013
- ==Response to a Signal from Question 1== I will use my signal from Question 1.2 KB (344 words) - 13:40, 26 September 2008
- == Example of Computation of Fourier series of a CT SIGNAL == The function y(t) in this example is the periodic continuous-time signal cos(t) such that1 KB (195 words) - 11:07, 16 September 2013
- A continuous-time Linear Time-Invariant (LTI) system defined for the purpose of this page wil where v(t) is an input signal dependent on the parameter of time.1 KB (233 words) - 17:43, 26 September 2008
- == Example of Computation of Fourier transform of a CT SIGNAL == Let the signal x(t) be equal to:1 KB (191 words) - 12:29, 16 September 2013
- Let the signal <math>X(\omega)</math> be equal to: The Inverse Fourier Transform of a signal in Continuous Time is:1,011 B (164 words) - 12:46, 16 September 2013
- The response to the input signal <math>z^n</math> is <math>H(z)z^n</math>, giving680 B (127 words) - 03:59, 15 October 2008
- '''Question:''' Compute the Fourier transform of the signal x(t) equal to: The Fourier Transform of a signal in Continuous Time is defined by:1 KB (188 words) - 11:09, 17 October 2008
- ...Fourier transform exists if the signal is absolutely integrable or if the signal has a finite number of discontinuities within any finite interval. (See Pag :This is useful for signals that fail to satisfy the previous properties of a signal that is guaranteed a Fourier Transform.3 KB (465 words) - 14:38, 24 October 2008
- What is it? Sampling is a process of measuring a CT signal x(t) at some specific values of time t. ...ample a continuous time signal x(t) at point t-1, t-2 and t-3. The sampled signal can represented by the formula <math>y[n] = x(nT)\,</math>2 KB (367 words) - 11:27, 7 November 2008
- ==Reconstructing a signal from its samples using Interpolation== ...an important procedure we know as interpolation we can obtain the original signal of the function.851 B (151 words) - 11:38, 8 November 2008
- ...ved by the use of a periodic impulse train multiplied by a continuous time signal, <math>x(t)</math>. The periodic impulse train, <math>p(t)</math> is refer3 KB (582 words) - 06:11, 16 September 2013
- ...continuous-time signal to discrete-time signal, process the discrete-time signal using a discrete-time system and convert it back to continuous time. ...and X(j<math>\omega\,</math>) be the continuous Fourier transform of that signal. Then,1 KB (214 words) - 08:00, 10 November 2008
- ...the uniformly spaced discrete samples are a complete representation of the signal if this bandwidth is less than half the sampling rate. ...signal and <math>X(W)\,</math> be the continuous Fourier transform of that signal2 KB (303 words) - 10:24, 10 November 2008
- Let <math>x(t)</math> be a signal with <math>X(\omega) = 0</math> when <math>|\omega| > \omega_m</math>. <math>\omega_m</math> Maximum frequencye for a band limited signal2 KB (349 words) - 12:09, 10 November 2008
- ...the uniformly spaced discrete samples are a complete representation of the signal if this bandwidth is less than half the sampling rate. ...signal and <math>X(w)\,</math> be the continuous Fourier transform of that signal (which exists if <math>x(t)\,</math> is square-integrable)2 KB (303 words) - 12:15, 10 November 2008
- ...AB. By use of sampling a continuous signal can be converted to a discrete signal, manipulated via a computer program and then converted back into a continuo1 KB (274 words) - 06:49, 16 September 2013
- ...u have used a good sampling rate, you should be able to reconstruct the CT signal without much fuss.829 B (155 words) - 16:53, 10 November 2008
- ...ation is defined by the authors of our book as the fitting of a continuous signal to a set of sample values, and is a commonly used procedure to reconstruct ...tion of the CT signal from the sampled signal approximates the original CT signal better.951 B (153 words) - 17:14, 10 November 2008
- Let x(t) be a signal with <math>\chi(\omega)=0</math> when <math>|\omega|<\omega_m</math>. P: A real-valued signal x(t) is known to be uniquely determined by its samples when the sampling fr2 KB (340 words) - 17:29, 10 November 2008
- ...actly, from samples. More so, interpolation is the fitting of a continuous signal to a set of sample values. Interpolation can also be defined as a specific1 KB (167 words) - 19:39, 10 November 2008
- The continuous-time Fourier transform provides us with a representation for signals as linear c ...the complex variable s, it is referred to as the Laplace transform of the signal. The complex variable zs can be written as <math>s=\sigma+j\omega</math>, w1 KB (183 words) - 17:02, 24 November 2008
- ...rm is used on continuous signal while z transform is used for the discrete signal. The z- transform of a general discrete signal x[n] is defined as2 KB (316 words) - 15:23, 3 December 2008
- #'''Signal Reconstruction Using Interpolation:''' the fitting of a continuous signal to a set of sample values ...nals (CD to MP3 albeit a complicated sampling algorithm, MP3 is less dense signal)21 KB (3,312 words) - 11:58, 5 December 2008
- :(c) an ability to determine the response of linear systems to any input signal convolution in the time domain. [1,2,4;a,e,k] :(e) an ability to determine the response of linear systems to any input signal by transformation to the frequency domain, multiplication, and inverse tran7 KB (1,017 words) - 10:05, 11 December 2008
- #'''Signal Reconstruction Using Interpolation:''' the fitting of a continuous signal to a set of sample values ...nals (CD to MP3 albeit a complicated sampling algorithm, MP3 is less dense signal)2 KB (254 words) - 07:05, 8 December 2008
- ##[[Signal Energy and Power_Old Kiwi]] ##[[Continuous-Time and Discrete-Time_Old Kiwi]]4 KB (531 words) - 11:32, 25 July 2008
- (a) The FT of <math>X(j\omega)</math> of a continuous-time signal x(t) is periodic (b) The FT of <math>X(e^{j\omega})</math> of a continuous-time signal x[n] is periodic4 KB (739 words) - 20:48, 30 July 2008
- .../math> of the signal x[n] is also periodic with period N. For the periodic signal x[n], find the values of <math>a_0,a_1,...,a_{N-1}.</math> Express your an 1)b)Evaluate the value of <math>(1/N)*\sum_{n=<N>}|x[n]|^2</math> for the signal x[n] given in part (a).4 KB (803 words) - 11:10, 22 July 2008
- Note: PM refers to the official course book, Digital Signal Processing, 3rd edition, J.G. Proakis and D.G. Manolakis. * Basic Signals and Signal Properties9 KB (1,237 words) - 09:29, 5 October 2009
- * Signal properties (even/odd, periodicity, power, energy, etc.)5 KB (643 words) - 11:55, 6 August 2009
- ...thcal{F}</math> of {a*x(t)+b*y(t)} will be equal to {a*X(w)+b*Y(w)} if the signal is truly linear. Signal <math>x(t)=1, 0<t\le1; 2, 1<t\le2; 0, else=u(t)+u(t-1)-2u(t-2)</math>2 KB (327 words) - 08:33, 8 July 2009
- '''== Time Shifting Property of Continuous-Time Fourier Series ==''' <br> When a time shift is applied to a periodic signal x(t), the period T of the signal is preserved.<br>1 KB (200 words) - 03:44, 9 July 2009
- ...the DT Fourier transform look like if the discretization represents the CT signal well?". Should we organize another recitation on that topic?--[[User:Mbou2 KB (375 words) - 04:11, 3 September 2009
- [[Category:signal processing]] ...frequency spectrum of a signal the faster we sample it. Naturally, if the signal changes much faster than the sampling rate, these changes will not be captu8 KB (1,452 words) - 06:49, 16 September 2013
- '''Q:''' What is a digital signal? '''A:''' A signal that can be represented by a sequence of 0's and 1's.1 KB (170 words) - 10:07, 23 September 2009
- ...tions caused by analog circuitry. One area that this can be applied is in signal reconstruction, where a low pass analog filter is used on the output of a d ...ed to relax requirements on analog low pass filter design while decreasing signal distortion.5 KB (840 words) - 19:08, 22 September 2009
- ...s time signal (consisting of infinite number of points) to a discrete time signal (finite points). This process enables the conversion of analog signals to ...period T). This can be achieved by multiplying the given continuous time signal by a train of dirac delta functions separated by the time period T. This c3 KB (527 words) - 11:50, 22 September 2009
- xc(t)=continuous time signal x[n]=discrete time signal1 KB (219 words) - 11:36, 23 September 2009
- ...ermines the number of pixels the camera uses to represent the "continuous" signal (e.g. a mountain, or your smiling significant other) that your digital came Thus the digital camera '''''samples''''' the continuous signal, with a period <math>T</math> (shutter speed) and "on" for length <math>tau6 KB (914 words) - 12:07, 22 October 2009
- ...e the magnitude of each frequency component's contribution to the original signal. Finally, the Fourier Transform is calculated to express these coefficients ...at is commonly referred to as the "spectrum" of the original discrete-time signal, x[n]. To demonstrate why this is the case, consider the following discrete8 KB (1,268 words) - 07:16, 23 September 2009
- ...s attenuating high frequency portions of the image unless they have a high signal energy (aka, they're significant in the reconstruction and representation o5 KB (850 words) - 09:00, 23 September 2009
- xc(t)=continuous time signal x[n]=discrete time signal1 KB (215 words) - 11:28, 23 September 2009
- *[[SignalMetricsFormula|Signal Metrics Definitions and Formulas]] (used in [[ECE301]], [[ECE438]]) **[[CT Fourier Transform (frequency in radians per time unit)|Continuous-time Fourier Transform Pairs and Properties]] (function of radial frequency- in3 KB (294 words) - 15:44, 12 March 2015
- keywords: energy, power, signal '''Signal Metrics Definitions and Formulas'''2 KB (307 words) - 14:54, 25 February 2015
- Table of Continuous-time (CT) Fourier Transform Pairs and Properties | signal (function of t)8 KB (1,130 words) - 11:45, 24 August 2016
- ...ignals_ECE301S11|Compute the norm of a continuous-time complex exponential signal (practice problem)]] from [[ECE301]] ..._signals_ECE301S11|Compute the norm of a discrete-time complex exponential signal (practice problem)]] from [[ECE301]]2 KB (293 words) - 05:21, 3 November 2011
- =About the Continuous-time Fourier Transform= ...008mboutin| Example of how to take the Fourier transform of a non-periodic signal]]2 KB (262 words) - 12:14, 21 February 2011
- ...ler's formula to compute the norm of a continuous-time complex exponential signal (practice problem)]] from [[ECE301]] ...Euler's formula to compute the norm of a discrete-time complex exponential signal (practice problem)]] from [[ECE301]]2 KB (249 words) - 18:27, 23 February 2015
- ...ectrical Engineers, the first person that comes to mind when someone says "SIGNAL PROCESSING" is Fourier. *Jean Baptiste Joseph Fourier (1768 - 1830) laid a rock-solid foundation for signal analysis, when he claimed that all (continuously differentiable) signals ca10 KB (1,646 words) - 11:26, 18 March 2013
- We'll start with the 2-dimensional rect(*) signal. Here's the 2-dimensional rect(x,y) function and its CSFT:<br><br>8 KB (1,397 words) - 11:23, 18 March 2013
- ...your concepts of Fourier and Z transforms should be absolutely clear for signal processing (DSP ECE 438).--[[User:Hlalwani|Hersh Lalwani]] 14:55, 11 Decemb ...sforms such as laplace, furiere and z-transform and signals and systems of continuous-time and discrete-time. However, it contains a lot of mathematics skill and some14 KB (2,366 words) - 17:32, 21 April 2013
- As everybody in the class seems to know quite well, the continuous-time signal <math> x(t) = cos(t) </math> is a periodic function with period <math> 2\pi ...pling <math> x(t) </math> every <math>T</math>, we obtain a discrete-time signal <math>f[n]</math>. However, <math>f[n]</math> is not necessarily periodic:4 KB (736 words) - 17:25, 23 April 2013
- ...teral z-Transform. Sampling, quantization, and discrete-time processing of continuous-time signals. Discrete-time nonlinear systems: median-type filters, threshold de <br/>iii. an ability to determine the response of linear systems to any input signal by convolution in the time domain.3 KB (394 words) - 07:08, 4 May 2010
- <br/><br/>9. Signal detection, signal estimation, cross-correlation functions<br/><br/>2 KB (231 words) - 07:20, 4 May 2010
- [[Category:digital signal processing]] ...hat can be used to describe almost anything in the world be it an electric signal or the stock market. Did you know that our brain picks up different frequen13 KB (2,348 words) - 13:25, 2 December 2011
- Note: PM refers to the official course book, Digital Signal Processing, 3rd edition, J.G. Proakis and D.G. Manolakis. Prentice Hall, 19 *Basic Signals and Signal Properties9 KB (1,331 words) - 07:15, 29 December 2010
- ...computation|A collective page to practice computing Fourier series of a CT signal]] ...putation_DT|A collective page to practice computing Fourier series of a DT signal]]2 KB (211 words) - 05:39, 26 September 2011
- Continuous-time Fourier Transform Pairs and Properties | signal (function of t)5 KB (687 words) - 21:01, 4 March 2015
- [[Category:Fourier series continuous-time]] ...pages contains exercises to practice computing the Fourier series of a CT signal =5 KB (797 words) - 09:43, 29 December 2010
- ...pages contains exercises to practice computing the Fourier series of a DT signal = *Fourier series of a discrete-time signal x[n] periodic with period N2 KB (355 words) - 09:44, 29 December 2010
- =Exercise: Compute the Fourier series coefficients of the following signal:= [[Recommended_exercise_Fourier_series_computation|More exercises on computing continuous-time Fourier series]]2 KB (324 words) - 08:08, 15 February 2011
- ...condition, the sampling frequency must be larger than the twice of maximum signal frequency, in order to avoid the aliasing when sampling. The frequency domain relationship betweeen a signal <math>x[n]</math> and its upsampled version <math>z[n]</math> can be shown3 KB (467 words) - 19:52, 20 September 2010
- ...es, a low-pass filter could be applied to this upsampling so to obtain the signal1 KB (220 words) - 16:07, 22 September 2010
- [[Category:digital signal processing]] <math>\text{ Sample a continuous signal x(t)=sin(}\omega t)\text{ with period of T, }</math>2 KB (373 words) - 10:41, 11 November 2011
- The highest frequency of the continuous signal is <math>f=\frac{\omega}{2\pi}</math>370 B (55 words) - 12:20, 29 September 2010
- =Exercise: Compute the Fourier series coefficients of the following periodic signal:= ...ary to state the period in the question, as one can figure it out from the signal itself. </span> --[[User:Mboutin|Mboutin]] 08:15, 29 September 2010 (UTC)6 KB (999 words) - 13:00, 16 September 2013
- *Fourier series of a continuous-time signal x(t) periodic with period T *Fourier series coefficients of a continuous-time signal x(t) periodic with period T2 KB (292 words) - 17:13, 30 September 2010
- *Fourier series of a continuous-time signal x(t) periodic with period T *Fourier series coefficients of a continuous-time signal x(t) periodic with period T1 KB (241 words) - 06:50, 30 September 2010
- ...transforms one complex-valued function of a real variable into another. In signal processing, the domain of the original function is typically in the time do4 KB (746 words) - 08:47, 11 November 2013
- Definition: let x[n] be a DT signal with Period N. Then, ...efficients of continuous periodic function x[n]? <br> The DFT of a sampled signal x[n] of length N is directly proportional to the Fourier series coefficient19 KB (3,208 words) - 11:23, 30 October 2011
- [[Category:signal]] keywords:signal energy, exercises1 KB (207 words) - 16:04, 25 February 2015
- [[Category:signal]] =Continuous-Time (Average) Signal Power=1 KB (220 words) - 10:49, 21 April 2015
- ...ar filtering view of the STFT. Then we obtained a formula to reconstruct a signal from its STFT. This concluded the material on speech processing. We then be933 B (122 words) - 09:32, 11 November 2011
- =About the Multiplication Property of the continuous-time Fourier transform= The multiplication property of the continuous-time Fourier transform can be stated as follows:751 B (105 words) - 16:17, 30 November 2010
- ...[Complex Exponential and Sinusoidal Amplitude Modulation|videos explaining signal modulation]]! ...problems to practice CT convlution, and two problems for practicing basic signal's properties. -pm18 KB (2,485 words) - 10:36, 11 November 2011
- Compute the Magnitude of the following continuous-time signals ...of the result. (This is basically what you are doing in a), but since the signal is real, it is equal to its conjugate.) A quick note though on the symbol <2 KB (292 words) - 16:17, 26 November 2013
- [[Category:signal]] [[Category:continuous-time signal]]4 KB (595 words) - 11:01, 21 April 2015
- ...\omega\right| > \omega_m </math>. Can one recover the signal x(t) from the signal <math class="inline"> y(t)=x(t) p(t-3) </math>, where ...omega)\right| > \omega_m </math>. Can one recover the signal x(t) from the signal <math class="inline"> y(t)=x(t) p(t-3) </math>, where900 B (158 words) - 16:06, 2 April 2011
- *[[SignalMetricsFormula|Signal Metrics Definitions and Formulas]] *[[CT Fourier Transform (frequency in radians per time unit)|Continuous-time Fourier Transform Pairs and Properties]] (function of <span class="texhtml"890 B (101 words) - 17:30, 21 April 2013
- ...olving|Practice Question]] on Computing the Fourier Series continuous-time signal= Obtain the Fourier series the CT signal4 KB (594 words) - 12:59, 16 September 2013
- *[[CT_Fourier_series_practice_problems_list|Problems on continuous-time Fourier series]] *[[CT_Fourier_transform_practice_problems_list|Problems on continuous-time Fourier transform]]12 KB (1,768 words) - 10:25, 22 January 2018
- ...ractice Question]] on Computing the Fourier Transform of a Continuous-time Signal = Compute the Fourier transform of the signal1 KB (197 words) - 10:25, 11 November 2011
- Today we obtained the formula for the Fourier transform of a periodic signal. We found that we cannot compute the Fourier transform of such signals usi We finished the lecture by discussing a few properties of the continuous-time Fourier transform.2 KB (215 words) - 14:12, 28 February 2011
- ...ractice Question]] on Computing the Fourier Transform of a Continuous-time Signal = Compute the Fourier transform of the signal2 KB (276 words) - 10:25, 11 November 2011
- ...ractice Question]] on Computing the Fourier Transform of a Continuous-time Signal = Compute the Fourier transform of the signal2 KB (355 words) - 10:26, 11 November 2011
- ...ractice Question]] on Computing the Fourier Transform of a Continuous-time Signal = Compute the Fourier transform of the signal853 B (122 words) - 10:26, 11 November 2011
- ...ractice Question]] on Computing the Fourier Transform of a Continuous-time Signal = Compute the Fourier transform of the signal1 KB (196 words) - 10:26, 11 November 2011
- Compute the Fourier transform of the continuous-time signal <math>x(t)=e^{-3 |t|}</math>. (Use the definition of the Fourier transform, Compute the Fourier transform of the signal4 KB (633 words) - 12:31, 2 March 2011
- ...irst part of today's lecture, we finished discussing the properties of the continuous-time Fourier transform. We then used these properties to obtain a simple express ...of shifted copies (shifted by <math>2 \pi k</math>, with k integer)of our signal.2 KB (346 words) - 14:13, 28 February 2011
- = [[:Category:Problem_solving|Practice Question]] on the Properties of the Continuous-time Fourier Transform = Let x(t) be a continuous time signal with Fourier transform <math class="inline">{\mathcal X} (\omega) </math>.2 KB (401 words) - 10:27, 11 November 2011
- .../span> for the computation of the Fourier transform of the continuous-time signal. Check every step of the computation and remove point for any mistakes. Tak ...r:red"> 15 pts </span> for the computation of the Fourier transform of the signal. Check every step of the computation and remove point for any mistakes. Tak7 KB (1,161 words) - 18:50, 4 March 2011
- ...(t). The physiological system being modeled, h(t), will convert this signal into output, y(t). For example, the blood clotting mechanism can be i ...rresponding to adenine, guanine, cytosine, and thymine.) Furthermore, this signal must be broken into distinct genes and decoded. These genes can be ma17 KB (2,368 words) - 10:53, 6 May 2012
- The signal <math class="inline"> x(t)= e^{j \pi t }\frac{\sin (\pi t)}{t} </math> is s ...omega \right| > \omega_m </math>. Can one recover the signal x(t) from the signal <math class="inline"> y(t)=x(t) p(t-3) </math>, where3 KB (451 words) - 06:40, 1 April 2011
- [[Category:signal processing]] = [[ECE438|ECE 438]]: Digital Signal Processing with Applications =10 KB (1,359 words) - 03:50, 31 August 2013
- [[Category:signal processing]] Note: PM refers to the official course book, Digital Signal Processing, 3rd edition, J.G. Proakis and D.G. Manolakis. Prentice Hall, 199 KB (1,341 words) - 03:52, 31 August 2013
- ...tal_signal_processing_practice_problems_list|Practice Question on "Digital Signal Processing"]]''' Topic: Continuous-time Fourier transform computation (in terms of frequency f in hertz)7 KB (1,302 words) - 09:45, 11 November 2013
- ...tal_signal_processing_practice_problems_list|Practice Question on "Digital Signal Processing"]]''' Topic: Continuous-time Fourier transform: from omega to f7 KB (1,143 words) - 09:44, 11 November 2013
- ...tal_signal_processing_practice_problems_list|Practice Question on "Digital Signal Processing"]]''' Topic: Continuous-time Fourier transform of a complex exponential3 KB (610 words) - 09:47, 11 November 2013
- ...ture 13, we discussed the possibility of an extra credit project involving signal resampling and filtering. ...p to figure out how to transform this signal into the (higher resolution) signal2 KB (243 words) - 06:23, 11 September 2013
- [[Category:signal processing]] Pick 5 different continuous-time signals x(t) (at least three of which should be band-limited, and at least2 KB (320 words) - 03:54, 31 August 2013
- ...computation|A collective page to practice computing Fourier series of a CT signal]] ...putation_DT|A collective page to practice computing Fourier series of a DT signal]]2 KB (212 words) - 05:44, 26 September 2011
- ...tal_signal_processing_practice_problems_list|Practice Question on "Digital Signal Processing"]]''' Give examples of continuous-time signals that are band-limited. (Justify your claim that they are band-limit2 KB (326 words) - 12:38, 26 November 2013
- '''Signal''' ...is a function, so when we say a continuous time signal or a discrete time signal we really mean continuous time functions and discrete time functions.3 KB (516 words) - 17:03, 2 December 2018
- [[Category:signal processing]]872 B (107 words) - 06:31, 11 September 2013
- ...tal_signal_processing_practice_problems_list|Practice Question on "Digital Signal Processing"]]''' ...n the exam, you could use the second approach if you were given a table of continuous-time fourier transform in which the Fourier transform of an exponential is given3 KB (576 words) - 12:57, 26 November 2013
- ...tal_signal_processing_practice_problems_list|Practice Question on "Digital Signal Processing"]]'''3 KB (487 words) - 12:57, 26 November 2013
- ...tal_signal_processing_practice_problems_list|Practice Question on "Digital Signal Processing"]]'''4 KB (678 words) - 12:58, 26 November 2013
- [[Category:signal processing]]2 KB (196 words) - 06:32, 11 September 2013
- ...tal_signal_processing_practice_problems_list|Practice Question on "Digital Signal Processing"]]''' Compute the discrete-space Fourier transform of the following signal:3 KB (473 words) - 12:59, 26 November 2013
- [[Category:Digital Signal Processing]] ...://www.projectrhea.org/learning/practice.php Practice Problems] on Digital Signal Processing6 KB (801 words) - 22:04, 19 April 2015
- [[Category:digital signal processing]] [[Category:signal processing]]2 KB (301 words) - 06:32, 11 September 2013
- = [[ECE]] 538: Digital Signal Processing I = *[[SignalMetricsFormula|Signal Metrics Definitions and Formulas]]1 KB (152 words) - 12:17, 24 February 2015
- Communication, Networking, Signal and Image Processing (CS) ...that <math class="inline">\mathbf{X}\left(t\right)</math> is a zero-mean, continuous-time, Gaussian white noise process with autocorrelation function <math class="in5 KB (735 words) - 01:17, 10 March 2015
- Communication, Networking, Signal and Image Processing (CS)4 KB (643 words) - 11:16, 10 March 2015
- Communication, Networking, Signal and Image Processing (CS)4 KB (572 words) - 10:24, 10 March 2015
- Communication, Networking, Signal and Image Processing (CS) Let <math class="inline">\mathbf{X}\left(t\right)</math> be a real continuous-time Gaussian random process. Show that its probabilistic behavior is completely5 KB (748 words) - 01:01, 10 March 2015
- Communication, Networking, Signal and Image Processing (CS) ...0"><span style="font-size: 19px;"><math>\color{blue} \text{Show that if a continuous-time Gaussian random process } \mathbf{X}(t) \text{ is wide-sense stationary, it4 KB (547 words) - 16:40, 30 March 2015
- Communication, Networking, Signal and Image Processing (CS) \text{Let } F(\mu,\nu) \text{ be the continuous-time Fourier transform of } f(x,y) \text{ given by}4 KB (665 words) - 10:25, 13 September 2013
- Communication, Networking, Signal and Image Processing (CS) ...000"><span style="font-size: 19px;"><math>\color{blue}\text{Show that if a continuous-time Gaussian random process } \mathbf{X}(t) \text{ is wide-sense stationary, it6 KB (932 words) - 10:30, 13 September 2013
- Communication, Networking, Signal and Image Processing (CS) \text{Let } F(\mu,\nu) \text{ be the continuous-time Fourier transform of } f(x,y) \text{ given by}17 KB (2,783 words) - 01:51, 31 March 2015
- *[[SignalMetricsFormula|Signal Metrics Definitions and Formulas]] *[[CT Fourier Transform (frequency in radians per time unit)|Continuous-time Fourier Transform Pairs and Properties]] (function of <span class="texhtml"2 KB (236 words) - 11:24, 21 September 2012
- To measure the worst case time delay from accelerometer signal input to orientation angle output at a macro scale (ie not by counting asse ...S. Smith, "DSP Software," ''The Scientist and Engineer's Guide to Digital Signal Processing''. <http://www.dspguide.com/ch4.htm>8 KB (1,176 words) - 15:15, 1 May 2016
- **[[SignalMetricsFormula|Signal Metrics Definitions and Formulas]] **[[CT_Fourier_Transform_(frequency_in_radians_per_time_unit)|Continuous-time Fourier Transform Pairs and Properties]] (function of <span class="texhtml"6 KB (799 words) - 10:10, 15 May 2013
- ...) = e^{-2}</math> at n=2, and so on. But because we have a constant input signal that effectively serves as a delta function at each time step, another impu ''<center>time-shifted continuous-time impulse responses due to a step function. (theoretically there should be an6 KB (991 words) - 15:18, 1 May 2016
- ...domain. It’s the output of In a LTI system when presented with a impulse signal input δ(t). In a LTI systems, impulse response is also equivalent to green2 KB (322 words) - 23:38, 10 March 2013
- ...hat the mean of the output random signal is equal to the mean of the input signal multiplied by the frequency response of the system evaluated at f=0. We als Note that we are now focusing only on continuous-time random processes for lack of time.3 KB (390 words) - 07:17, 24 April 2013
- ::↳ Eigen-Signal Analysis and Examples ...T is for continuous time signals. Let <math>x(n)</math> be a discrete time signal. Then, its DTFT, <math>X(e^{j\omega})</math> is given by <br/>10 KB (1,726 words) - 07:26, 26 February 2014
- [[Category:digital signal processing]] [[Category:signal processing]]9 KB (1,353 words) - 09:04, 11 November 2013
- **[[SignalMetricsFormula|Signal Metrics Definitions and Formulas]] **[[CT_Fourier_Transform_(frequency_in_radians_per_time_unit)|Continuous-time Fourier Transform Pairs and Properties]] (function of <span class="texhtml"4 KB (480 words) - 18:57, 10 December 2013
- [[Category:signal processing]] ...in terms of <math>\omega</math>, which you have seen in [[ECE301]], to the continuous-time Fourier transform in terms of f. We then saw a few important properties of3 KB (505 words) - 06:56, 2 September 2013
- *[[Audio_Signal_Filtering|Audio Signal Filtering]]3 KB (389 words) - 18:10, 23 February 2015
- on continuous-time Fourier transform ==Collectively solved problems on continuous-time Fourier transform==7 KB (966 words) - 18:17, 23 February 2015
- on continuous-time Fourier series ==Collectively solved problems on continuous-time Fourier series==7 KB (992 words) - 18:16, 23 February 2015
- ...x(t) be a continuous-time signal and let y[n]=x(nT) be a sampling of that signal with period T>0. We would like to interpolate the samples (i.e., "connect t ...imited interpolation of the samples (i.e., an expression for a continuous signal z(t) in terms of the samples y[n]). (Do not simply write down the formula;2 KB (362 words) - 13:59, 26 September 2013
- [[Category:signal processing]] ''' [[ECE438| ECE438: Digital Signal Processing with Applications]]'''1,002 B (119 words) - 05:58, 28 October 2013
- [[Category:signal processing]] ''' [[ECE438| ECE438: Digital Signal Processing with Applications]]'''4 KB (471 words) - 19:34, 9 February 2015
- [[Category:signal processing]] *[[2D_rect|2D rect signal]]2 KB (309 words) - 12:13, 7 November 2013
- [[Category:signal processing]] *[[2D_rect|2D rect signal]]2 KB (274 words) - 07:11, 11 November 2013
- Communication, Networking, Signal and Image Processing (CS)3 KB (449 words) - 21:36, 5 August 2018
- <font size="4">Communication, Networking, Signal and Image Processing (CS)</font>6 KB (995 words) - 09:21, 15 August 2014
- ** Be able to calculate the Fourier series coefficients of a period CT signal (DT Fourier series will NOT be on the exam). (3.28a(subparts abc), 3.22, 3. ...the frequency response of a system, find the FS coefficients of the output signal. (3.13, 3.14, Quiz 3)6 KB (765 words) - 13:35, 4 August 2016
- =Lab Wiki: [[2014_Fall_ECE_438_Boutin|ECE 438: Digital Signal Processing With Applications]], Fall 2014=2 KB (380 words) - 08:18, 2 December 2014
- [[Category:digital signal processing]] [[Category:signal processing]]9 KB (1,320 words) - 04:46, 11 September 2014
- [[Category:signal processing]] ...in terms of <math>\omega</math>, which you have seen in [[ECE301]], to the continuous-time Fourier transform in terms of f. We then saw a few important properties of3 KB (393 words) - 06:37, 27 August 2014
- [[Category:signal processing]] ...led'. But this process is a little different from sampling. The continuous signal will become discrete after sampling while it will still be continuous after5 KB (768 words) - 18:51, 16 March 2015
- ...nderstand the relation between comb vs original signal and rep vs original signal.7 KB (1,226 words) - 05:30, 15 October 2014
- ...x(t) be a continuous-time signal and let y[n]=x(nT) be a sampling of that signal with period T>0. We would like to interpolate the samples (i.e., "connect t ...imited interpolation of the samples (i.e., an expression for a continuous signal z(t) in terms of the samples y[n]). (Do not simply write down the formula;3 KB (462 words) - 09:43, 18 September 2014
- ...x(t) be a continuous-time signal and let y[n]=x(nT) be a sampling of that signal with period T>0. We would like to interpolate the samples (i.e., "connect t ...imited interpolation of the samples (i.e., an expression for a continuous signal z(t) in terms of the samples y[n]). (Do not simply write down the formula;7 KB (1,178 words) - 20:16, 18 December 2014
- [[Category:signal processing]] The discrete time fourier transform (DTFT) of a finite energy aperiodic signal x[n] can be given by the equation listed below. IT is a representation in t5 KB (862 words) - 20:02, 16 March 2015
- [[Category:signal processing]] ...g this cosine with period T (frequency <math>f_{s}=1/T</math>, the sampled signal <math>x[n]</math> can be written as <math>x[n]=cos(\frac{2 \pi f n}{T})</ma5 KB (801 words) - 20:04, 16 March 2015
- [[Category:signal processing]] ...nly be reconstructed perfectly from its sampling <math>x_s(t)</math>if the continuous-time Fourier Transform (CTFT) of <math>x(t)</math> is zero for all magnitudes of10 KB (1,650 words) - 19:04, 16 March 2015
- [[Category:signal processing]] ...cy domain view of the relationship between a signal and a sampling of that signal4 KB (732 words) - 19:07, 16 March 2015
- [[Category:signal processing]] ...cy domain view of the relationship between a signal and a sampling of that signal5 KB (852 words) - 09:58, 14 March 2015
- ...cy domain view of the relationship between a signal and a sampling of that signal </font> ...ship between a signal, and a sampling of that signal. Essentially, given a signal x(t), we are going to take a look at the similarities and differences in X(4 KB (599 words) - 09:58, 14 March 2015
- #Derivation of DTFT of downsampled signal<br> ...ure provides definition of downsampling, derives DTFT of downsampled signal and demonstrates it in a frequency domain. Also, it explains process of dec7 KB (1,035 words) - 19:07, 16 March 2015
- ...to eliminate the possibility of aliasing and distorting the reconstructed signal. Begin with x(t) as a continuous time signal with <math>x_1[n]= x(T_1*n)</math> being its discrete time sampling.4 KB (566 words) - 09:59, 14 March 2015
- ...cy domain view of the relationship between a signal and a sampling of that signal </font> ...f original signal x(t), sampled signal x<sub>s</sub>(t) and discrete signal x<sub>d</sub>[n]. Graphs in frequency domain help to understand this4 KB (621 words) - 05:40, 15 October 2014
- =Lab Wiki: [[2015_Fall_ECE_438_Boutin|ECE 438: Digital Signal Processing With Applications]], Fall 2015=2 KB (303 words) - 13:45, 5 October 2015
- [[Category:digital signal processing]] [[Category:signal processing]]10 KB (1,356 words) - 13:19, 19 October 2015
- =Lab Wiki: [[2015_Spring_ECE_438_Ersoy|ECE 438: Digital Signal Processing With Applications]], Spring 2015=2 KB (384 words) - 11:44, 21 April 2015
- Communication, Networking, Signal and Image Processing (CS)2 KB (331 words) - 17:37, 13 March 2015
- Communication, Networking, Signal and Image Processing (CS)2 KB (302 words) - 17:38, 13 March 2015
- Communication, Networking, Signal and Image Processing (CS)2 KB (284 words) - 17:39, 13 March 2015
- Communication, Networking, Signal and Image Processing (CS) Let <math class="inline">\mathbf{X}\left(t\right)</math> be a real continuous-time Gaussian random process. Show that its probabilistic behavior is completely874 B (125 words) - 01:04, 10 March 2015
- Communication, Networking, Signal and Image Processing (CS) ...that <math class="inline">\mathbf{X}\left(t\right)</math> is a zero-mean, continuous-time, Gaussian white noise process with autocorrelation function <math class="in2 KB (318 words) - 01:05, 10 March 2015
- Communication, Networking, Signal and Image Processing (CS)2 KB (366 words) - 01:36, 10 March 2015
- Communication, Networking, Signal and Image Processing (CS) ...that <math class="inline">\mathbf{X}\left(t\right)</math> is a zero-mean, continuous-time, Gaussian white noise process with autocorrelation function <math class="in6 KB (1,002 words) - 01:38, 10 March 2015
- Communication, Networking, Signal and Image Processing (CS)3 KB (454 words) - 10:25, 10 March 2015
- Communication, Networking, Signal and Image Processing (CS) Assume that <math>\mathbf{X}(t)</math> is a zero-mean continuous-time Gaussian white noise process with autocorrelation function8 KB (1,336 words) - 01:53, 31 March 2015
- [[Category:signal]] [[Category:continuous-time signal]]2 KB (290 words) - 15:29, 21 April 2015
- Chap 4. Continuous-Time Fourier Transform : [[Media:CTFT_Table.pdf|Continuous-Time Fourier Transform Table]] / [[Media:freq_allocation.pdf|US Frequency Alloca6 KB (748 words) - 21:35, 10 August 2015
- [[Category:signal processing]] ...tal signals and digital systems. We looked at some applications of digital signal processing, including3 KB (445 words) - 08:57, 28 August 2015
- ...e second goal of this homework is to learn different ways to reconstruct a signal. Consider the signal <math>x(t)=5 \text{sinc } ( \frac{t-7}{2} ).</math>3 KB (554 words) - 12:10, 11 September 2015
- ...be accomplished in an equivalent fashion by processing a sampling of that signal. ...t off frequency of 800Hz and a gain of 7. Let's call this desired filtered signal y(t).3 KB (499 words) - 16:04, 22 September 2015
- ...t off frequency of 800Hz and a gain of 7. Let's call this desired filtered signal y(t). ...such a way that a band-limited interpolation of the processed (output) DT signal would be the same as y(t)? Answer yes/no. If you answered yes, explain how.3 KB (475 words) - 15:23, 20 October 2015
- a) Obtain the Fourier transform X(f) of the signal and sketch the graph of |X(f)|. b) What is the Nyquist rate <math>f_0</math> for this signal?7 KB (1,181 words) - 19:17, 19 October 2015
- ...''aliasing'' that occurs when converting a continuous signal to a discrete signal via sampling. ...rmation applied to an aperiodic, discrete signal in order to represent the signal in terms of it's various spectral (frequency) components. It is defined as:12 KB (2,004 words) - 20:37, 2 December 2015
- [[Category:digital signal processing]] [[Category:signal processing]]10 KB (1,357 words) - 17:02, 14 September 2016
- =Lab Wiki: [[2016_Fall_ECE_438_Boutin|ECE 438: Digital Signal Processing With Applications]], Fall 2016=2 KB (301 words) - 14:05, 26 September 2016
- The goal of this homework is to learn two different ways to reconstruct a signal. ...x(t) be a continuous-time signal and let y[n]=x(nT) be a sampling of that signal with period T>0. We would like to interpolate the samples (i.e., "connect t2 KB (346 words) - 11:10, 16 September 2016
- *go over the relationship between DT signal processing and CT signal processing (for a simple filter) once more, this time with a focus on the e Let x[n] be a DT signal. Let z[n]=x[2n] be a downsampling of x[n]. Let y[n] be an upsampling of x[n4 KB (636 words) - 08:16, 21 September 2016
- [[Category:digital signal processing]] [[Category:signal processing]]10 KB (1,357 words) - 09:45, 8 January 2017
- =Lab Wiki: [[2017_Spring_ECE_438_Boutin|ECE 438: Digital Signal Processing With Applications]], Spring 2017=2 KB (325 words) - 18:20, 30 March 2017
- :b) understand the two different signal reconstruction methods we saw in class. ...ignal. Assuming that the highest frequency in the electroelectrocardiogram signal are at 2200 Hz, what criteria would you use to select the sampling frequen4 KB (658 words) - 14:50, 1 February 2017
- 3. A continuous time signal is such that <math> \chi(f) </math> is 0 when |f| > 3 KHz. You would like a ...mple exists with a sampling rate of 9000 samples/sec. Can you process this signal to make a band limited interpolation? If no, explain why. If yes, explain h7 KB (1,194 words) - 19:21, 24 April 2017
- ...region of convergence and translating a discrete signal into a continuous signal relate directly to the Laurent Series. ...like the Taylor Series, it builds a continuous function out of a discrete signal. This is the main way that the Laurent Series is related to DSP: its abilit6 KB (931 words) - 23:40, 23 April 2017
- =Lab Wiki: [[2017_Fall_ECE_438_Boutin|ECE 438: Digital Signal Processing With Applications]], Fall 2017=3 KB (418 words) - 21:57, 7 January 2018
- ...ncy-domain, one is primarily concerned with the information contained in a signal's component sinusoids. ...e integrated impulse response and will show how the filter will affect the signal in the time-domain. On the other hand, the frequency response will show how6 KB (897 words) - 16:44, 7 December 2017
- [[Category:signal]] [[Category:continuous-time signal]]2 KB (373 words) - 10:09, 22 January 2018
- [[Category:signal]] [[Category:continuous-time signal]]2 KB (229 words) - 10:22, 22 January 2018
- Biomedical signal processing aims at extracting significant information from physiological si ...sease, and earlier detection of both heart attacks and strokes. Biomedical signal processing is most useful in the critical care setting due to patient data12 KB (1,702 words) - 20:48, 9 April 2018
- ...quires Nlog(N). DFT is not the same as DTFT. Both start with discrete-time signal, but DFT produces a discrete frequency domain representation while the DTFT ...analysis. A common use of FFT’s is to find the frequency component of a signal buried in a noisy time domain. Given the MATLAB code bellow, a graph will b3 KB (555 words) - 22:02, 2 December 2018
- Communications and Signal Processing5 KB (910 words) - 03:02, 24 February 2019
- ...ideas developed in Calculus courses and expands on them with the focus on signal observation, analysis, and creation. It is unlike any other course I have t3 KB (583 words) - 21:07, 24 April 2019
- ...ideas developed in Calculus courses and expands on them with the focus on signal observation, analysis, and creation. It is unlike any other course I have t4 KB (644 words) - 11:22, 30 April 2019
- =Lab wiki for ECE 438:Digital Signal Processing With Applications, Fall 2019=4 KB (572 words) - 11:16, 3 December 2019
- [[Category:digital signal processing]] [[Category:signal processing]]10 KB (1,356 words) - 18:52, 20 August 2019
- ...ignal directly, this is not possible in reality since storing a real-world signal would require an infinite amount of memory. Consequently, all signals are s With this information, we can express the sampling of a CT signal <math>x(t)</math> in terms of its sampling period T:16 KB (2,611 words) - 14:11, 12 November 2019
- The convolution forms the backbone of signal processing, but what are some direct applications of it? In this page, we w7 KB (1,006 words) - 22:10, 22 December 2019
- ...lled amplitudes. In signal processing, there are discrete-time signals and continuous-time signals. When time is viewed as a discrete variable, then any function of t ...ractical cases, one can use Nyquist's Theorem to ensure that all essential signal information is collected, while not wasting effort measuring with too much2 KB (375 words) - 21:03, 6 December 2020
