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- d. Filter represented by this difference equation is IIR. Because the transfer functi2 KB (441 words) - 05:42, 28 October 2010
- Q2. Consider a causal FIR filter of length M = 2 with impulse response Q5. Define a two-zero band-stop filter such that3 KB (462 words) - 10:42, 11 November 2011
- Suppose the transfer function of the filter has the form Where <math>z_1,z_2</math> are zeros of the filter.2 KB (279 words) - 17:23, 3 November 2010
- Q1. Consider a causal FIR filter of length M = 2 with impulse response3 KB (561 words) - 10:43, 11 November 2011
- Q4. Consider a 3X3 FIR filter with coefficients h[m,n] <br/> a. Find a difference equation that can be used to implement this filter.<br/>3 KB (398 words) - 10:43, 11 November 2011
- ...that <math class="inline">h\left(t\right)</math> acts as a crude low-pass filter that attenuates high-frequency power.3 KB (498 words) - 07:16, 1 December 2010
File:Pasted23.png Crude low-pass filter(728 × 337 (31 KB)) - 12:21, 19 November 2010- d. Describe how the filter behaves when <math>\lambda</math> is positive and large. <br/> e. Describe how the filter behaves when <math>\lambda</math> is negative and bigger than -1. <br/>3 KB (515 words) - 10:43, 11 November 2011
- d. For large values of <math>\lambda</math>, the filter performs sharpening.<br/> e. For -1 < <math>\lambda</math> < 0, the filter performs blurring.<br/>2 KB (275 words) - 13:34, 28 November 2010
- ...quency domain perspective. We looked an an example in detail (the low-pass filter illlustrated on top of [[ECE_438_Fall_2009_mboutin_plotCSFTofbasicfilters|t808 B (107 words) - 10:56, 29 November 2010
- ...ral input signal <math>x[m,n]</math> we get the difference equation of the filter. b. Place the center of filter (i.e. where m=0,n=0) upon the pixel of image. Multiply h[m,n] with x[m,n] o2 KB (391 words) - 07:16, 30 November 2010
- ...lting in huge disturbance to the game, I feel strong obligated to design a filter to remove the noise. Each filter is used to remove corresponding frequency component.3 KB (409 words) - 08:53, 11 November 2013
- ...ms]] from [[2011 Spring ECE 301 Boutin|ECE301]]!) are utilized to convert, filter, and combine these signals and produce the images used in diagnostics.17 KB (2,368 words) - 10:53, 6 May 2012
- ...y that the Fourier transform is a non-zero constant multiple of a low-pass filter with gain 1 and cutoff <math>3 \pi</math> and conclude from there; you woul3 KB (431 words) - 10:28, 11 November 2011
- ...'c''</sub>''t'').</span> Then feed the resulting signal through a low pass filter with a gain of 2 and a cutoff frequency of <span class="texhtml">ω<sub>''c b) Multiply by cos(w<sub>c</sub>t) then pass it through a Low Pass Filter with a gain of 2 and a cutoff f of w<sub>c</sub>2 KB (400 words) - 10:31, 11 November 2011
- ...ignal can be recovered by filtering the sampled signal using the following filter: ...DT, one must first convert the samples to a pulse-train, and then low-pass filter. -pm </font>9 KB (1,462 words) - 07:01, 22 April 2011
- ...</sub> = 1000π</span> and gain 2. The frequency response of this low pass filter is: Note that the cut-off frequency of the low pass filter can actually be anywhere between <span class="texhtml">ω<sub>''M''</sub></12 KB (2,109 words) - 05:58, 22 April 2011
- **[[Practice_Question_5_ECE438F10|Practice Question 5 (filter design)]] ....m.zip zpgui3.m] A MATLAB GUI showing the effect of poles and zeros during filter design.10 KB (1,359 words) - 03:50, 31 August 2013
- *[[ECE438_Week9_Quiz|LTI system and filter design]] <br/>900 B (121 words) - 10:39, 11 November 2011
- *Week (7)-8: Filtering (Systems defined by Difference equations, Filter Design, DFT view of Filtering) ***Prof. Bouman's lecture notes on digital Filter design: [https://engineering.purdue.edu/~bouman/ece438/lecture/module_1/1.79 KB (1,341 words) - 03:52, 31 August 2013
- =Image processing on an Android phone - Lowpass filter an Image - C++ code= ...ore used to. The filtering itself is not really complicated: We just use a filter in form of a matrix and perform a convolution. As this is not really an iss3 KB (486 words) - 11:58, 20 April 2012
- ...revious lecture, we observed that, under certain circumstances, a low-pass filter could be applied to this upsampling so to obtain the signal1 KB (213 words) - 06:24, 11 September 2013
- ...this by computing the frequency response and the transfer function of that filter. In particular, we noted how the location of the poles and the zeros of the [[Category:Filter]]998 B (143 words) - 06:27, 11 September 2013
- **[[Practice_Question_5_ECE438F10|Practice Question 5 (filter design)]]9 KB (1,273 words) - 20:52, 15 October 2011
- ...n the location of the poles and the zeros of the transfer function of this filter and the amplitude of its frequency response. [[Category:Filter]]953 B (132 words) - 06:27, 11 September 2013
- equation (moving average filter) :a. Find the impulse response h[n] for this filter. Is it of finite or infinite duration?5 KB (916 words) - 03:56, 31 August 2013
File:Zpgui3.m.zip Matlab GUI showing the effect of the placement of poles and zeros during filter design.(2 KB) - 17:47, 22 October 2011- Today we discussed the relevance of "filter design" in today's world, including some open problems for which research i [[Category:Filter]]1 KB (221 words) - 06:28, 11 September 2013
- ...e unit impulse response of an ideal filter in order to obtain a causal FIR filter. A MATLAB plot of the example presented in class can be viewed on [[ECE_4381 KB (164 words) - 06:30, 11 September 2013
- ::#low pass filter the repeated part7 KB (1,108 words) - 06:02, 23 September 2014
- A LPF (low-pass-filter) will usually be used before down-sampling to reduce aliasing. In this  ...f 4, 8, and 16. In this project we are using FIR (finite impulse response) filter.<br>The audio signal we use is part of Waving Flag, the theme song of 201010 KB (1,707 words) - 10:44, 6 May 2012
- *Filter design **[[Practice_Question_5_ECE438F10|Practice question on filter design]]6 KB (801 words) - 22:04, 19 April 2015
- ...n]. We then proceed to demonstrate how to use the formula using an average filter and a 6x6 digital image. The issue of the boundary conditions was discussed2 KB (301 words) - 06:32, 11 September 2013
- ...sample by factor of 5 then down sample by factor 3. To avoid aliasing, the filter was build by MATLAB embedded function "fir1" with order= 20, cut-of frequen2 KB (389 words) - 06:37, 25 September 2013
- ...arate it. We then considered another filter (edge detector). Although that filter is not separable, we were able to write it as a sum of two separable filter2 KB (213 words) - 06:32, 11 September 2013
- Consider the following FIR filter: a) Write a difference equation that can be used to implement this filter.2 KB (270 words) - 03:59, 31 August 2013
- ...other type of filter introduced by Perona and Malik. We observed that this filter is not linear and that it allows one to smooth out an image without blurrin1 KB (157 words) - 06:33, 11 September 2013
- Therefore the filter can be separate into two 1-D filters.3 KB (355 words) - 13:42, 4 December 2011
- =Image processing on an Android phone - Lowpass filter an Image - Java code= ...roject was to lowpass filter an image on an Android phone using a Gaussian filter. Therefore it should be possible to either take a picture with the integrat7 KB (1,278 words) - 11:57, 20 April 2012
- ...tion, signal mixing, encoding and decoding of audio signals, and real-time filter implementation. Additionally, I was involved with the development of a filt4 KB (676 words) - 12:21, 9 February 2012
- ...ng a proof of the visit to a doctor with a date and time on it, so it will filter out such students who use this excuse frequently and know all the details h6 KB (1,023 words) - 09:24, 16 March 2012
- ...cy filtering removes noise, but also blurs images as a result. The unsharp filter accentuates the edges of images, in an emboss like feature. The parts of th1 KB (196 words) - 17:45, 21 April 2013
- so filter out them. /* Filter in daily returns on earning reports dates */11 KB (1,577 words) - 08:35, 23 April 2012
- 3. \text{ Multiply step 2 by the filter } H(\rho) = |\rho| = f_c \left [ rect(\frac{f}{2f_c}) - \Lambda(\frac{f}{f_ 2. \text{ Filter the projections } \rho_{\theta}(r) \text{ with } h(r) \text{, where } H(\rh17 KB (2,783 words) - 01:51, 31 March 2015
- ...t from probabilistic noise-reducing filters such as the Bayesian or Kalman filter.8 KB (1,176 words) - 15:15, 1 May 2016
- ** Low Pass Filter: Smoothing (less sharp edges or details but reduces some static noise) ** High Pass Filter: Sharping (clear edge and enhance details but also emphasize noise)3 KB (555 words) - 08:09, 9 April 2013
- b) Create Gaussian filter of size 5x5 with mean 0 and standard deviation 3. c) Plot Fourier Transform of filter’s impulse response in 3D.4 KB (573 words) - 10:15, 15 May 2013
- ...l has probability of {1/10,2/10,4/10,2/10,1/10}. The signal goes through a filter, Z=2X^2+1. Z: output after the filter<br>2 KB (299 words) - 18:13, 27 February 2013
- filter <math>h(m,n)</math> is a <math>(2N+1)\times(2N+1)</math> filter, and for each location we need 2 multiplies, so in total, we need <math>2(2 ...ated offline, if we consider that <math> a_j b_i </math> are merged in the filter <math> h(m,n)</math>, then will need <math> (2N+1)^2 </math> multiplies to4 KB (739 words) - 10:07, 13 September 2013
- •filter = imfilter(picture,G); imshow(filter)2 KB (305 words) - 07:35, 11 March 2013
