Presentation is loading. Please wait.

Presentation is loading. Please wait.

2/17/2007DSP Course-IUST-Spring Semester 1 Digital Signal Processing Electrical Engineering Department Iran University of Science & Tech.

Published byMeghan Price Modified over 7 years ago

Similar presentations

Presentation on theme: "2/17/2007DSP Course-IUST-Spring Semester 1 Digital Signal Processing Electrical Engineering Department Iran University of Science & Tech."— Presentation transcript:

1 2/17/2007DSP Course-IUST-Spring Semester 1 Digital Signal Processing Electrical Engineering Department Iran University of Science & Tech.

2 DSP Course-IUST-Spring Semester2 2/17/2007 Digital Signal Processing Topic 9: Filter Design: FIR 1. Windowed Impulse Response 2. Window Shapes 3. Design by Iterative Optimization

3 DSP Course-IUST-Spring Semester3 2/17/2007 1. FIR Filter Design

4 DSP Course-IUST-Spring Semester4 2/17/2007 Least Integral-Squared Error

5 DSP Course-IUST-Spring Semester5 2/17/2007 Least Integral-Squared Error

6 DSP Course-IUST-Spring Semester6 2/17/2007 Least Integral-Squared Error

7 DSP Course-IUST-Spring Semester7 2/17/2007 Approximating Ideal Filters

8 DSP Course-IUST-Spring Semester8 2/17/2007 Approximating Ideal Filters

9 DSP Course-IUST-Spring Semester9 2/17/2007 Gibbs Phenomenon

10 DSP Course-IUST-Spring Semester10 2/17/2007 Where Gibbs comes from

11 DSP Course-IUST-Spring Semester11 2/17/2007 Where Gibbs comes from

12 DSP Course-IUST-Spring Semester12 2/17/2007 Where Gibbs comes from

13 DSP Course-IUST-Spring Semester13 2/17/2007 2. Window Shapes for Filters

14 DSP Course-IUST-Spring Semester14 2/17/2007 Window Shapes for FIR Filters

15 DSP Course-IUST-Spring Semester15 2/17/2007 Window Shapes for FIR Filters

16 DSP Course-IUST-Spring Semester16 2/17/2007 Adjustable Windows

17 DSP Course-IUST-Spring Semester17 2/17/2007 Windowed Filter Example

18 DSP Course-IUST-Spring Semester18 2/17/2007 Windowed Filter Example

19 DSP Course-IUST-Spring Semester19 2/17/2007 Freq. Resp. (FR) Arithmetic

20 DSP Course-IUST-Spring Semester20 2/17/2007 3. Iterative FIR Filter Design

21 DSP Course-IUST-Spring Semester21 2/17/2007 Error Criteria

22 DSP Course-IUST-Spring Semester22 2/17/2007 Minimax FIR Filters

23 DSP Course-IUST-Spring Semester23 2/17/2007 Minimax FIR Filters

24 DSP Course-IUST-Spring Semester24 2/17/2007 Minimax FIR Filters

25 DSP Course-IUST-Spring Semester25 2/17/2007 Alternation Theorem

26 DSP Course-IUST-Spring Semester26 2/17/2007 Alternation Theorem

27 DSP Course-IUST-Spring Semester27 2/17/2007 Alternation Theorem

28 DSP Course-IUST-Spring Semester28 2/17/2007 Alternation Theorem

29 DSP Course-IUST-Spring Semester29 2/17/2007 Parks-McClellan Algorithm

30 DSP Course-IUST-Spring Semester30 2/17/2007 Parks-McClellan Algorithm

31 DSP Course-IUST-Spring Semester31 2/17/2007 Parks-McClellan Algorithm

Download ppt "2/17/2007DSP Course-IUST-Spring Semester 1 Digital Signal Processing Electrical Engineering Department Iran University of Science & Tech."

Similar presentations

DSP C5000 Chapter 16 Adaptive Filter Implementation Copyright © 2003 Texas Instruments. All rights reserved.

DSP C5000 Chapter 16 Adaptive Filter Implementation Copyright © 2003 Texas Instruments. All rights reserved.
Compare ideal Interpolation filter and interpolation by LSE FIR filter(Final) Advisor : Dr. Yung-AN Kao Student: Ying Chun Chen.

Compare ideal Interpolation filter and interpolation by LSE FIR filter(Final) Advisor : Dr. Yung-AN Kao Student: Ying Chun Chen.
Equiripple Filters A filter which has the Smallest Maximum Approximation Error among all filters over the frequencies of interest: Define: where.

Equiripple Filters A filter which has the Smallest Maximum Approximation Error among all filters over the frequencies of interest: Define: where.
2/17/2007DSP Course-IUST-Spring Semester 1 Digital Signal Processing Electrical Engineering Department Iran University of Science & Tech.

2/17/2007DSP Course-IUST-Spring Semester 1 Digital Signal Processing Electrical Engineering Department Iran University of Science & Tech.
Ideal Filters One of the reasons why we design a filter is to remove disturbances Filter SIGNAL NOISE We discriminate between signal and noise in terms.

Ideal Filters One of the reasons why we design a filter is to remove disturbances Filter SIGNAL NOISE We discriminate between signal and noise in terms.
Department of electrical and computer engineering An Equalization Technique for High Rate OFDM Systems Mehdi Basiri.

Department of electrical and computer engineering An Equalization Technique for High Rate OFDM Systems Mehdi Basiri.
Parks-McClellan FIR Filter Design

Parks-McClellan FIR Filter Design
Sampling, Reconstruction, and Elementary Digital Filters R.C. Maher ECEN4002/5002 DSP Laboratory Spring 2002.

Sampling, Reconstruction, and Elementary Digital Filters R.C. Maher ECEN4002/5002 DSP Laboratory Spring 2002.
DSP Group, EE, Caltech, Pasadena CA IIR Ultra-Wideband Pulse Shaper Design Chun-yang Chen and P.P. Vaidyananthan California Institute of Technology.

DSP Group, EE, Caltech, Pasadena CA IIR Ultra-Wideband Pulse Shaper Design Chun-yang Chen and P.P. Vaidyananthan California Institute of Technology.
AGC DSP AGC DSP Professor A G Constantinides 1 Digital Filter Specifications Only the magnitude approximation problem Four basic types of ideal filters.

AGC DSP AGC DSP Professor A G Constantinides 1 Digital Filter Specifications Only the magnitude approximation problem Four basic types of ideal filters.
EEE422 Signals and Systems Laboratory Filters (FIR) Kevin D. Donohue Electrical and Computer Engineering University of Kentucky.

EEE422 Signals and Systems Laboratory Filters (FIR) Kevin D. Donohue Electrical and Computer Engineering University of Kentucky.
ELEN 5346/4304 DSP and Filter Design Fall 2008 1 Lecture 11: LTI FIR filter design Instructor: Dr. Gleb V. Tcheslavski Contact:

ELEN 5346/4304 DSP and Filter Design Fall Lecture 11: LTI FIR filter design Instructor: Dr. Gleb V. Tcheslavski Contact:
Digital Signal Processing

Digital Signal Processing
DSP for Dummies aka How to turn this (actual raw sonar trace) Into this.. (filtered sonar data)

DSP for Dummies aka How to turn this (actual raw sonar trace) Into this.. (filtered sonar data)
1 Lecture 5: March 20, 2007 Topics: 1. Design of Equiripple Linear-Phase FIR Digital Filters (cont.) 2. Comparison of Design Methods for Linear- Phase.

1 Lecture 5: March 20, 2007 Topics: 1. Design of Equiripple Linear-Phase FIR Digital Filters (cont.) 2. Comparison of Design Methods for Linear- Phase.
Filter Design Techniques

Filter Design Techniques
IIR Filter design (cf. Shenoi, 2006) The transfer function of the IIR filter is given by Its frequency responses are (where w is the normalized frequency.

IIR Filter design (cf. Shenoi, 2006) The transfer function of the IIR filter is given by Its frequency responses are (where w is the normalized frequency.
Digital Signal Processing FIR Filter Design

Digital Signal Processing FIR Filter Design
Copyright ©2010, ©1999, ©1989 by Pearson Education, Inc. All rights reserved. Discrete-Time Signal Processing, Third Edition Alan V. Oppenheim Ronald W.

Copyright ©2010, ©1999, ©1989 by Pearson Education, Inc. All rights reserved. Discrete-Time Signal Processing, Third Edition Alan V. Oppenheim Ronald W.
1 Chapter 7 Filter Design Techniques (cont.). 2 Optimum Approximation Criterion (1)  We have discussed design of FIR filters by windowing, which is straightforward.

1 Chapter 7 Filter Design Techniques (cont.). 2 Optimum Approximation Criterion (1)  We have discussed design of FIR filters by windowing, which is straightforward.

Similar presentations

Ads by Google