dspcourse plan 2012

7/27/2019 DSPCourse Plan 2012

1/6

MIT/GEN/F-05/R0

DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING

COURSE PLAN

Department : E&C

Subject : ECE-303 : Digital Signal Processing

Semester & branch : 5th Semester E & C

Name of the faculty : Dr. KUMARA SHAMA, Mr. SHASHI KUMAR.G.S.,

Mr. ANANTHAKRISHNA T, Mr. SAMPATH KUMAR

No of contact hours/week : 04

Assignment portion

Assignment no. Topics

1 L1-L16

2 L17-L36

3 L37-L48

Test portion

Test no. Topics

1 L1-L16

2 L17-L36

Submitted by: SHASHI KUMAR G S

Date:

Approved by: Dr. K .PRABHAKAR NAYAK

(Signature of HOD)Date:

Page 1 of6

MANIPAL INSTITUTE OF TECHNOLOGY(A constituent college of Manipal University, Manipal)

Manipal Karnataka 576 104


2/6

MIT/GEN/F-05/R0

Course Objectives

At the end of this course, the student will be able to:

CO1- Analyze any given signal in z domain and check for stability and other features.CO2- Understand the importance of transforms and frequency domain analysis.

CO3- Calculate the Fourier transform of any signal.

CO4- Design FIR filters for a given problem.CO5- Design IIR filters for a given problem.

CO6- Design structures for implementing FIR and IIR filters.

CO7- Calculate the power spectrum of any signal

LectureNo.

Topics to be covered

1 Review of Signals and Systems, Time analysis of Signals andSystems

2 Frequency analysis of Signals and Systems

3 Review of Z-Transform, Unilateral z-transform, solution of differenceequations

4 Tutorial

5 Analysis of LTI system in z-domain-system function

6 pole-zero analysis, stability

7 Frequency domain sampling and reconstruction of discretetime signals DFT

8 Tutorial

9 Properties of the DFT

10 Use of DFT in linear filtering , Filtering of long datasequences

11 Efficient computation of the DFT-FFT algorithm,

12 Tutorial

13 Radix-2 DIT-FFT and DIF-FFT

Page 2 of6


3/6

MIT/GEN/F-05/R0

14 In-place computation, Pipeline FFT, Goertzel algorithm

15 Structures for IIR systems Direct form-I & II

16 Tutorial

17 IIR Parallel & Cascade structure

18 Structures for FIR systems, Direct form structure Cascadeform structure, Frequency sampling structure

19 Lattice structures for FIR

20 Tutorial

21 Lattice ladder structures for IIR

22 Finite word length effect (Qualitative )

23 Classical design of IIR filters by impulse invariance method

24 Tutorial

25 Bilinear transformation, Matched Z-Transform

26 Characteristics of Butterworth, Chebyshev & elliptic filters

27 Design of Butterworth filter

28 Tutorial

29 Chebyshev filter design

30 Spectral transformations

31 Direct design of IIR filters

32 Tutorial

33 Design of digital FIR filters-general considerations

Page 3 of6


4/6

MIT/GEN/F-05/R0

34 Characteristics of Linear phase FIR filter

35 Symmetric and anti-symmetric impulse response

36 Tutorial

37 Design of FIR filters using windows

38 Design of FIR filters using windows conti

39 Frequency sampling design , Optimum design

40 Tutorial

41 Estimation of power spectra from finite duration of

observation of signals

42 Non parametric methods of PSD estimation:Periodogram, Bartlett ,Welch methods

43 Blackman and Tukey methods (qualitative analysis).

44 Tutorial

45 Parametric methods of PSD estimation: AR, ARMA and MA modeling.

46 Yule-Walker & Burg methods for AR model parameters.

47 Least square and sequential estimation method of AR modeling (qualitative analysis)

48 Tutorial

Reference Books:

1. Proakis J.G and.Manolakis D.G. Mimitris D. (2003) Introduction to Digital

Signal ProcessingPrentice Hall, India2. Oppenheim A.V.and Schafer R.W. (2003) Discrete Time Signal Processing,

Pearson education.

3. Ifeachar and Jervis (2003) Digital Signal Processing: A Practical approachPearson education, Asia

4. Rabiner L.R and Gold D.J (1988) Theory and applications of digital signal

processingPrentice Hall, India

Page 4 of6


5/6

MIT/GEN/F-05/R0

5. Sanjit Mitra K(2001) Digital Signal Processing: A computer based approach,

TMH

6. Johnson J.R,(1994) Introduction to Digital Signal Processing Prentice Hall,

India

ECE-303 DIGITAL SIGNAL PROCESSING [3 1 0 4]

Total number of lecturehours 48

Course Objectives

At the end of this course, the student will be able to:

CO1- Analyze any given signal in z domain and check for stability and other features.

CO2- Understand the importance of transforms and frequency domain analysis.CO3- Calculate the Fourier transform of any signal.

CO4- Design FIR filters for a given problem.CO5- Design IIR filters for a given problem.CO6- Design structures for implementing FIR and IIR filters.

CO7- Calculate the power spectrum of any signal

Course Description

Review: Time and frequency analysis of signals and systems.

[3]

Z-transform and its application to the analysis of LTI systems: Review of z-

transform, unilateral z-transform, solution of difference equations, Analysis of LTI

system in z-domain-system function, pole-zero analysis, stability[5]

Page 5 of6


6/6

MIT/GEN/F-05/R0

Discrete Fourier Transform: Frequency domain sampling and reconstruction of

discrete time signals DFT, properties of the DFT, use of DFT in linear filtering,

filtering of long data sequences, DFT as linear transformation, Efficient computation ofthe DFT- FFT Algorithms, Radix 2 DITFFT and DIFFFT, in-place computation, pipeline

FFT, Goertzel Algorithm.

[8]

Implementation of Discrete time Systems: Structures for FIR systems Direct form,cascade form, Frequency sampling and lattice structures. Structures for IIR systems

Direct form, cascade and parallel form, lattice ladder structures. Finite word length

effects. [8]

Design of IIR filters: Classical design by impulse invariance, bilinear transformation and

matched Z transform, characteristics and design of commonly used filters butter worth,

Chebyshev and elliptic filters, Spectral transformations, Direct design of IIR filters.

[8]

Design of Digital FIR Filters:

General considerations, Linear phase FIR Filters, Symmetric and anti-symmetric impulse

response, Design using windows, frequency sampling design, Optimum design.

[8]

Power Spectrum Estimation:

Estimation of power spectra from Finite duration of observation of signals. Non-

parametric methods of PSD estimation: Periodogram, Bartlett, Welch, Blackman andTukey methods (qualitative analysis). Parametric methods of PSD estimation: AR,

ARMA and MA modeling, Yule-Walker, Burg method, least square estimation and

sequential estimation method of AR modeling (qualitative analysis).[8]

Page 6 of6

dspcourse plan 2012

Documents