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  • ECE 301 Fall 2007 mboutin Simplified View of Cascaded Systems
    ...ignal would, and writing all the transforms or "things" that happen to the signal using different variables, then we go back and substitute so it all works o
    3 KB (486 words) - 11:10, 8 December 2008
  • ECE 301 Fall 2007 mboutin Definition of Sampling Theorem
    A band-limited signal can be recovered by sampling if the sampling frequency <math> \omega_s </ma
    589 B (78 words) - 13:08, 8 December 2008
  • ECE 301 Fall 2007 mboutin Convolution
    This is an example of convolution done two ways on a fairly simple general signal.
    3 KB (549 words) - 10:37, 30 January 2011
  • ECE 301 Fall 2007 mboutin DT Fourier Series in Matlab
    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
  • ECE 301 Fall 2007 mboutin Convergence of Fourier Transforms
    and let <math> x(t)\ </math> denote the signal obtained by using <math> X(j\omega)\ </math> in the right hand side of Equa
    1 KB (227 words) - 11:54, 10 December 2008
  • ECE 301 Fall 2007 mboutin Sifting Property
    ...an then apply the 'effect' of the system to each individual impulse of the signal, sum them, and find the resulting output.
    2 KB (322 words) - 17:27, 23 April 2013
  • ECE 301 Fall 2007 mboutin Common Questions on FS/FT Answered By Mimi
    ...hey are for periodic signals also. The formula for transforming a periodic signal is (I believe) the first one on the table. :: Fourier Transform is for all signal. It represents signals as an integral of complex exponentials.
    1 KB (186 words) - 17:25, 23 April 2013
  • ECE 301 Fall 2007 mboutin Meaning of Fourier Transform
    ...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
  • ECE 301 Fall 2007 mboutin Multidimension Fourier Transform
    ...sion for CT signals, and performing a summation for each dimension in a DT signal.
    2 KB (303 words) - 10:13, 12 December 2008
  • ECE 301 Fall 2007 mboutin Nyquist Example
    ...pled signal that is band limited to about 20kHz, then we should sample the signal at twice that frequency.
    925 B (151 words) - 17:28, 23 April 2013
  • ECE 301 Fall 2007 mboutin Sampling Theorem
    The sampling theorem tells us that we can perfectly reconstruct a signal if the following two conditions are observed: # The signal has a finite bandwidth B. (meaning the signal is band limited)
    3 KB (591 words) - 17:24, 23 April 2013
  • ECE 301 Fall 2007 mboutin Animated Aliasing Example
    ...sampled greater than the Nyquist Rate in order to reconstruct the original signal. The effect of undersampling, or sampling at a rate below that of the Nyqui ...ponds to a frequency of .2 rev/sec. This frequency is the frequency of the signal. The small red dot is just an indicator on a part of the wheel to make it e
    3 KB (446 words) - 06:21, 18 September 2013
  • ECE 301 Fall 2007 mboutin Sampling Theorem Def
    ...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
  • ECE 301 Fall 2007 mboutin Your Sampling Theorem
    Let <math> x(t)\ </math> be a BAND-LIMITED signal with <math> X(\omega) = 0\ </math> for <math> |\omega| > \omega_m\ </math>.
    739 B (108 words) - 12:43, 18 December 2008
  • ECE 301 Fall 2007 mboutin Sound in Matlab
    : <code>Plot(Y)</code> Plots vector Y (useful to visualize an audio signal). Plotting at different frequencies: ...ode>x=y ( 1 : N : length(y) );</code> will create a vector x, which is the signal Y at 1/N of its original frequency. (takes every N element of y and puts in
    725 B (116 words) - 13:10, 18 December 2008
  • Research Group List
    *[[ECE:CNSIP area| Communication, Networking, Signal and Image Processing (CNSIP) area (from ECE)]]
    493 B (74 words) - 11:24, 25 May 2009
  • List of Course Wikis
    :[[2015_Spring_ECE_438_Ersoy|ECE438: "Digital SIgnal Processing", Prof. Ersoy]] :[[2014_Fall_ECE_438_Boutin|ECE438: "Digital SIgnal Processing"]]
    13 KB (1,570 words) - 13:53, 7 August 2018
  • ECE 438 professor Boutin Spring 2009 Course Details
    =ECE 438: Digital Signal Processing with Applications=
    558 B (80 words) - 09:55, 27 February 2009
  • Lecture Schedule (ECE438BoutinSpring09)
    | align="right" style="padding-right: 1em;" | Wednesday || 01/14/09 || Signal types, characteristics, transformations || 1.1.1-1.1.3 || CT and DT signals
    6 KB (689 words) - 07:59, 2 August 2010
  • Main Page ECE301Fall2008mboutin
    *[[lecture1_ECE301Fall2008mboutin|Lecture 1]]: Intro; Example of DT signal (text) and system (enigma machine). *[[Lecture2_ECE301Fall2008mboutin|Lecture 2]]: Example of CT signal (sound); Creating sounds in Matlab; Example of linear system.
    5 KB (720 words) - 06:10, 16 September 2013
  • Main Page ECE301Fall2008chihw
    I am trying to figure out how to compute the norm of the DT signal
    2 KB (396 words) - 16:53, 23 April 2013
  • CNSIP plan of study
    * A typical plan of study for a first semester Signal Processing Grad Student (MS or PhD) is: ECE600, ECE538, MA511 ==If you are a direct PhD student interested in the signal processing area==
    2 KB (308 words) - 13:06, 30 September 2009
  • ECE 438 Spring 2009 mboutin Course Notes
    [[Category:signal processing]]
    865 B (78 words) - 06:37, 16 September 2013
  • CourseNotes1 (BoutinSpring2009)
    [[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
  • ECE 438 Spring 2009 mboutin Symbols
    *<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
  • CourseNotes2 (BoutinSpring2009)
    [[Category:signal processing]] <li>Signal Characteristics</li>
    3 KB (508 words) - 06:43, 16 September 2013
  • CourseNotes3 (BoutinSpring2009)
    [[Category:signal processing]] <p>Comb operator multiplies a signal by an "impulse train".
    2 KB (408 words) - 06:43, 16 September 2013
  • CourseNotes4 (BoutinSpring2009)
    [[Category:signal processing]]
    2 KB (359 words) - 06:43, 16 September 2013
  • Table of Formulas and Properties ECE301Fall2008mboutin
    *[[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
  • Tektronix presentation February 2009
    ...is is an advanced capture, process and display technology which enables RF signal analysis never before possible. Featured capabilities, discussed and demons *Automatic RF signal identification
    967 B (123 words) - 12:47, 5 February 2009
  • Hw3 comments (ECE438BoutinSpring09)
    ...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
  • CourseNotes6 (BoutinSpring2009)
    [[Category:signal processing]]
    769 B (105 words) - 06:44, 16 September 2013
  • HW 3 Question 4 mlo
    ...ng: when you upsample after having downsampled, you introduce zeros in the signal that were not previously there. To undo a downsampling, you have to use an
    2 KB (383 words) - 21:03, 10 February 2009
  • HW 3 Question 3
    ...at starts at -1e-4 and goes to 1e-4. The ideal sampler creates a discrete signal with 5 points each 5e-5 apart.
    844 B (152 words) - 18:26, 11 February 2009
  • Getting X(w) from X(f)
    ...e relationship between the FT of a signal and the FT of a sampling of that signal. Anybdy sees a mistake? Perhaps one can rewrite this so it becomes a bit cl
    2 KB (374 words) - 12:35, 17 February 2009
  • What you want to know for Exam 1
    *Basic properties of signal and systems <li>Don't forget the different signal's metrics! --[[User:Mboutin|Mboutin]] 16:15, 17 February 2009 (UTC)</li>
    710 B (115 words) - 14:35, 17 February 2009
  • CourseNotes16 (BoutinSpring2009)
    [[Category:signal processing]] <p>use DFT to approximate <math>X(a)</math> for a DT signal x(n)
    2 KB (376 words) - 06:44, 16 September 2013
  • HW 4 Question 3
    ...o union between the ROCs, then it's null such that there is no ROC for the signal --[[User:Mlo|Mlo]] 15:18, 24 February 2009 (UTC)
    549 B (90 words) - 08:37, 26 February 2009
  • Hw4 comments (ECE438BoutinSpring09)
    ...rect in time. In frequency, this is multiplication of the spectrum of the signal with the spectrum of the rect (which is a sinc). This is effectively a coa
    906 B (143 words) - 12:40, 4 March 2009
  • CourseNotes20 (BoutinSpring2009)
    [[Category:signal processing]]
    3 KB (522 words) - 06:45, 16 September 2013
  • Interactive CNSIP area presentation
    ** Signal Processing
    258 B (29 words) - 08:56, 27 March 2009
  • CourseNotes30 (BoutinSpring2009)
    [[Category:signal processing]]
    2 KB (324 words) - 06:45, 16 September 2013
  • Reading guide (ECE438BoutinSpring2009)
    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
  • Meta Course List
    :[[ECE438|ECE438: "Digital Signal Processing with Applications"]] *[[ECE438|ECE 438]]: "Digital Signal Processing with Applications"
    4 KB (474 words) - 07:08, 4 November 2013
  • ECE438 (BoutinFall2009)
    =Rhea Section for [[ECE438|ECE 438: Digital Signal Processing with Applications]] Professor [[User:mboutin|Boutin]], Fall 2009
    7 KB (1,067 words) - 12:05, 25 June 2010
  • Homework 1 ECE301Fall2008mboutin
    * [[HW1.5 Nicholas Browdues - Signal Power and Energy_ECE301Fall2008mboutin]] * [[HW1.5 Ben Laskowski - Signal Power and Energy_ECE301Fall2008mboutin]]
    24 KB (3,272 words) - 06:58, 1 September 2010
  • Lecture2 ECE301Fall2008mboutin
    == 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
  • HW1.1 Hetong Li ECE301Fall2008mboutin
    %as we replace t with 2t,so double the time in signal function %which also means double the frequency of each signal
    2 KB (347 words) - 17:52, 3 September 2008
  • HW1.2 Hetong Li ECE301Fall2008mboutin
    jpbak=flipud(jp); %reverse the signal
    544 B (83 words) - 18:34, 1 September 2008
  • HW1.5 Ben Laskowski - Signal Power and Energy ECE301Fall2008mboutin
    [[Category:signal]] Compute the power and energy of the signal
    1,007 B (151 words) - 13:45, 24 February 2015

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