Line 70: Line 70:
 
Post a link to your slecture page below the relevant topic. If you want to reserve a particular topic, write your name/nickname below the topic. Please no more than 4 students per topic. To build your slecture page, you should use the following templates.  
 
Post a link to your slecture page below the relevant topic. If you want to reserve a particular topic, write your name/nickname below the topic. Please no more than 4 students per topic. To build your slecture page, you should use the following templates.  
 
*[[Slecture_template_ECE438F14|Template for text slecture]]
 
*[[Slecture_template_ECE438F14|Template for text slecture]]
*[[Slecture_template_video_ECE438F14|Template for video slecture]] (Coming soon)
+
*[[Slecture_template_video_ECE438F14|Template for video slecture]]  
  
  
*Topic 1: Fourier transform as a function of frequency <math>\omega</math> versus  Fourier transform as a function of frequency <math>f</math> (in hertz). (Make sure to give some examples, including some signal whose FT cannot be computed directly because the intergral diverges, as well as some signal whose FT involves some Dirac delta(s). For that signal whose FT involves some Dirac delta(s), compute the FT two different ways: 1) by starting from the ECE301 FT pair and making a change of variable, and 2) by direct computation. Observe that the expressions for the FT are different. Then point out that one can transform one expression into the other using the scaling property of the Dirac delta.)  
+
*'''Topic 1''': Fourier transform as a function of frequency <math>\omega</math> versus  Fourier transform as a function of frequency <math>f</math> (in hertz). (Make sure to give some examples, including some signal whose FT cannot be computed directly because the intergral diverges, as well as some signal whose FT involves some Dirac delta(s). For that signal whose FT involves some Dirac delta(s), compute the FT two different ways: 1) by starting from the ECE301 FT pair and making a change of variable, and 2) by direct computation. Observe that the expressions for the FT are different. Then point out that one can transform one expression into the other using the scaling property of the Dirac delta.)  
 +
**[[slecture_CTFT_Xiaozhe|Text slecture ]]by Xiaozhe
 
**link to slecture page
 
**link to slecture page
**[[slecture_CTFT_Xiaozhe|text slecture ]]by Xiaozhe
 
 
**link to slecture page
 
**link to slecture page
 +
*''' Topic 2''': Definition of the "rep" and "comb" operators
 
**link to slecture page
 
**link to slecture page
* Topic 2: Definition of the "rep" and "comb" operators
 
 
**link to slecture page
 
**link to slecture page
**link to slecture page
+
*''' Topic 3''': Fourier transform of "rep" and "comb"
* Topic 3: Fourier transform of "rep" and "comb"
+
 
**[[Fourier_Transform_rep_com_Ben_ECE438_slecture|Video slecture]] by Ben  
 
**[[Fourier_Transform_rep_com_Ben_ECE438_slecture|Video slecture]] by Ben  
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
*Topic 4: Discrete-time Fourier transform (DTFT): definition, periodicity property, example (computation of DTFT of a complex exponential)
+
*'''Topic 4''': Discrete-time Fourier transform (DTFT): definition, periodicity property, example (computation of DTFT of a complex exponential)
**link to slecture page
+
**link to slecture page
+
**link to slecture page
+
*Topic 5: Discrete-time Fourier transform (DTFT) of a sampled cosine. Case 1) sampling rate above Nyquist rate, Case 2) sampling rate below Nyquist rate
+
**link to slecture page
+
**link to slecture page
+
**link to slecture page
+
*Topic 6: Z-transform: definition, example (computation of a z-transform using geometric series)
+
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
*Topic 7: How to compute an inverse z-transform using power series expansion (give at least one example)
+
*'''Topic 5''': Discrete-time Fourier transform (DTFT) of a sampled cosine. Case 1) sampling rate above Nyquist rate, Case 2) sampling rate below Nyquist rate
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
*Topic 8: Nyquist Theorem, with proof and example
+
*'''Topic 6''': Nyquist Theorem, with proof and example
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
*Topic 9 Frequency domain view of the relationship between a signal and a sampling of that signal
+
*'''Topic 7''': Frequency domain view of the relationship between a signal and a sampling of that signal
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
*Topic 10: Frequency domain view of downsampling
+
*'''Topic 8''': Frequency domain view of downsampling
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
*Topic 11: Frequency domain view of upsampling
+
*'''Topic 9''': Frequency domain view of upsampling
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page
 
**link to slecture page

Revision as of 05:59, 3 September 2014


ECE 438: Digital Signal Processing with Applications

Professor Boutin, Fall 2014


Message area:


Course Information

  • Instructor: Prof. Mimi
  • Teaching Assistant: Trey Shenk
    • Email: shenkt at purdue dot you know what
  • Teaching Assistant: Ikbeom Jang
    • Email: jang69 at purdue dot you know what
  • Course Outline (Approximate schedule with detailed reference list)
  • Course Syllabus
  • Important Dates:
    • Test 1: Friday October 10, 2014
    • Test 2: Friday December 5, 2014
    • Final, TBA

Labs

Here


Resources


Lecture Blog

Lecture 1, 2, 3 ,4 ,5 ,6 ,7 ,8 ,9 ,10 ,11 ,12 ,13 ,14 ,15 ,16 ,17 ,18 ,19 ,20 ,21 ,22 ,23 ,24 ,25 ,26 ,27 ,28 ,29 ,30 ,31 ,32 ,33 ,34 ,35 ,36 ,37 ,38 ,39 ,40 ,41 ,42 ,43 ,44, final exam .


Homework


Slectures

Post a link to your slecture page below the relevant topic. If you want to reserve a particular topic, write your name/nickname below the topic. Please no more than 4 students per topic. To build your slecture page, you should use the following templates.


  • Topic 1: Fourier transform as a function of frequency $ \omega $ versus Fourier transform as a function of frequency $ f $ (in hertz). (Make sure to give some examples, including some signal whose FT cannot be computed directly because the intergral diverges, as well as some signal whose FT involves some Dirac delta(s). For that signal whose FT involves some Dirac delta(s), compute the FT two different ways: 1) by starting from the ECE301 FT pair and making a change of variable, and 2) by direct computation. Observe that the expressions for the FT are different. Then point out that one can transform one expression into the other using the scaling property of the Dirac delta.)
  • Topic 2: Definition of the "rep" and "comb" operators
    • link to slecture page
    • link to slecture page
  • Topic 3: Fourier transform of "rep" and "comb"
  • Topic 4: Discrete-time Fourier transform (DTFT): definition, periodicity property, example (computation of DTFT of a complex exponential)
    • link to slecture page
    • link to slecture page
    • link to slecture page
  • Topic 5: Discrete-time Fourier transform (DTFT) of a sampled cosine. Case 1) sampling rate above Nyquist rate, Case 2) sampling rate below Nyquist rate
    • link to slecture page
    • link to slecture page
    • link to slecture page
  • Topic 6: Nyquist Theorem, with proof and example
    • link to slecture page
    • link to slecture page
    • link to slecture page
  • Topic 7: Frequency domain view of the relationship between a signal and a sampling of that signal
    • link to slecture page
    • link to slecture page
    • link to slecture page
  • Topic 8: Frequency domain view of downsampling
    • link to slecture page
    • link to slecture page
    • link to slecture page
  • Topic 9: Frequency domain view of upsampling
    • link to slecture page
    • link to slecture page
    • link to slecture page

A bonus point opportunity

Students in ECE438 Fall 2014 have the opportunity to earn up to a 3% bonus by contributing a Rhea page on a subject related to digital signal processing. To pick a subject, simply write your name next to it. Your page will be graded based on content as well as interactions with other people (page views, comments/questions on the page, etc.). The number of links to other courses and subjects will also be taken into account: the more the merrier! Please do not simply copy the lecture notes and do not plagiarize. Read Rhea's copyright policy before proceeding.


Topic Number Topic Description Student Name
1 Something related to CT or DT Fourier transform Name
2 Something related to Z-transform Name
3 Something related to discrete Fourier transform Name
4 Something related to CSFT Name
5 Something related to Quantization Name
6 Student blog Name (s)
7 Pick your own topic Name (s)

Back to ECE438

Alumni Liaison

Ph.D. 2007, working on developing cool imaging technologies for digital cameras, camera phones, and video surveillance cameras.

Buyue Zhang