Digital Signal Processing - Course Handout

BIRLA INSTITUTE OF TECHNOLOGY & SCIENCE, PILANI

WORK INTEGRATED LEARNING PROGRAMMES

Digital Learning

Part A:  Content Design

Course Title	Digital Signal Processing
Course No(s)	ES ZG573/ MEL ZG573
Credit Units	3
Credit Model	1-0-2
Course Author	Dr. Satya Sudhakar Y & Dr. S. K. sahoo
Version No	0.3
Date	Last updated on 21/06/2016

Course Objectives

No	Course Objective
CO1	Review the basics of Signals & Systems.
CO2	Introduce Computationally efficient algorithms that are required for the core signal processing operations found in most applications.
CO3	Introduce few important DSP Processor Architecture blocks which evolved based on an insight into the Algorithms learnt.

Teaching methodology

The teaching methodology to be used are:

a) Lectures

b) Simple MATLAB based illustrations.

c) Group Discussions & Analysis

Text Book(s)

T1	“Digital signal processing: principles, algorithms, and application-4/E." J. G. Proakis and D.G. Manolakis
T2	Discrete-Time Signal Processing, 3/E, Alan V. Oppenheim, Ronald W. Schafer

Reference Book(s) & other resources

R1	“Digital Signal processing: A computer based approach” by Sanjit K. Mitra
R2	E.C. Ifeachor and B.W. Jervis. Digital signal processing: a practical approach. Pearson Education, 2002.
R3	Digital Signal Processing by Srinivasan & Avtar Singh

Modular Content Structure

1 Introduction

1.1 Signals, Systems, and Signal Processing

1.2 Classification of Signals

1.3 The Concept of Frequency in Continuous-Time and Discrete-Time Signals

1.4 Analog-to-Digital and Digital-to-Analog Conversion

2 Discrete-Time Signals And Systems

2.1 Discrete-Time Signals

2.2 Discrete-Time Systems

2.3 Analysis of Discrete-Time Linear Time-Invariant systems

2.4 Discrete-Time Systems Described by Difference Equations

3 The Z-Transform and Its Application to the Analysis Of LTI Systems

3.1 The z-Transform

3.2 Properties of the z-Transform

3.3 Rational z-Transforms

3.4 Inversion of the z-Transform (From Look Up Table Only)

3.5 Analysis of Linear Time Invariant Systems in the z-Domain

4 The Discrete Fourier Transform: Its Properties And Applications

4.1 Frequency Domain Sampling: The Discrete Fourier Transform

4.2 Properties of the DFT

4.3 Linear Filtering Methods Based on the DFT

4.4 Frequency Analysis of Signals Using the DFT

4.5 The Discrete Cosine Transform

5 Efficient Computation of the DFT: Fast Fourier Transform Algorithms

5.1 Efficient Computation of the DFT: FFT Algorithms

5.2 Applications of FFT Algorithms

5.3 A Linear Filtering Approach to Computation of the DFT

6 Design of Digital Filers

6.1 Analog filter design

6.2 Design of IIR Filters From Analog Filters

6.3 Design of FIR Filters

6.4 Frequency Transformations

7 Implementation Of Discrete-Time Systems

7.1 Structures for the Realization of Discrete-Time Systems

7.2 Structures for FIR Systems

7.3 Structures for IIR Systems

7.4 Representation of Numbers

8 Multirate Digital Signal Processing

8.1 Introduction

8.2 Decimation by a Factor D

8.3 Interpolation by a Factor I

8.4 Sampling Rate Conversion by a Rational Factor I/D

8.5 Implementation of Sampling Rate Conversion

9 DSP Architectures

9.1 Generic Structure

9.2 ALU, AGU, MAC, Barrel Shifter units

Learning Outcomes:

No	Learning Outcomes
LO1	Student will understand/review the basics of DSP.
LO2	Student should gain understanding about the Four Flavours of the Fourier Transforms CTFT, DTFT, CTFS, DTFS and use of FFT get frequency domain of DT signal.
LO3	Students should gain detailed understanding the basic operations (1) Convolution (2) Correlation and their Spectral Significance.
LO4	Students should gain detailed understanding about LTI Sytems, time domain operation and DIGITAL Filter Design
LO5	With the acquired knowledge, students should be able to organize the computations into systematic Algorithms and then be able to asses the complexity, data access requirements of these algorithms. This eventually leads to the appreciation of DSP architectures and their programming.

Experiential learning components

Assumption : MATLAB/OCTAVE is available for each session.

Live MATLAB Demos to visualize the computations of some key algorithms.

1.      Radix-2 DIT FFT & DIF FFT

2.      DCT and IDCT

3.      Linear Convolution

4.      Circular Convolution

5.      Use of FFT to find the spectrum of known signal. Understanding and estimating the frequency resolution.

6.      Design of FIR filter and response finding

7.      Design of IIR filter and response finding

8.      Use of FDA tool in Matlab for filter designing

9.      Use of Simulink to design a filter.

Additional documentation

1.      Types of assessments:

EC1: Assignment / Quiz

EC2: Mide-sem examination (closed book)

EC3: Comprehensive examination (open book)

Part B: Course Handout

Academic Term	First Semester 2017-2018
Course Title	Digital Signal Processing
Course No	ES ZG573 / MEL ZG573
Lead Instructor	Dr. Mary Lourde R

Session Number	List of Topic Title (from content structure in Part A)	Topic # (from content structure in Part A)	Text/Ref Book/external resource
1	1.1 Signals, Systems, and Signal Processing 1.2 Classification of Signals 1.3 The Concept of Frequency in Continuous-Time and Discrete-Time Signals 1.4 Analog-to-Digital and Digital-to-Analog Conversion	1.1 to 1.4	T1, T2 (relevant)
2	2 Discrete-Time Signals and Systems 2.1 Discrete-Time Signals 2.2 Discrete-Time Systems 2.3 Analysis of Discrete-Time Linear Time-Invariant systems 2.4 Discrete-Time Systems Described by Difference Equations	2.1 to 2.4	T1, T2 (relevant)
3	4 The Discrete Fourier Transform: Its Properties And Applications 4.1Frequency Domain Sampling: The Discrete Fourier Transform 4.2 Properties of the DFT 4.3 Linear Filtering Methods Based on the DFT 4.5 Frequency Analysis of Signals Using the DFT 4.5 The Discrete Cosine Transform	4.1 to 4.5	T1, T2 (relevant)
4	5 Efficient Computation of The DFT: Fast Fourier Transform Algorithms 5.1 Efficient Computation of the DFT: FFT Algorithms (DIT and DIF, Split Radix)	5.1	T1, T2 (relevant)
5	5.2 Applications of FFT Algorithms 5.3 A Linear Filtering Approach to Computation of the DFT	5.2-5.3	T1, T2 (relevant)
6	3.1 The z-Transform 3.2 Properties of the z-Transform 6.3 Rational z-Transforms 3.4 Inversion of the z-Transform 3.5 Analysis of Linear Time Invariant Systems in the z-Domain	3.1 to 3.5	T1, T2 (relevant)
7	6 Design of Digital Filers 6.1 General Considerations, Design of FIR Filters using Windows method	6.1	T1, T2 (relevant)
8	6.1 Design of FIR Filters using Frequency sampling method, Design of different type of other FIR filters	6.1	T1, T2 (relevant)
9	6.2 Different Analog filters and Design of IIR Filters From Analog Filters	6.2, 6.3	T1, T2 (relevant)
10	6.4 Frequency Transformations	6.4	T1, T2 (relevant)
11	7 Implementation of Discrete-Time Systems 7.1 Structures for the Realization of Discrete-Time Systems 7.2 Structures for FIR Systems	7.1, 7.2	T1, T2 (relevant)
12	7.3 Structures for IIR Systems 7.4 Representation of Numbers	7.3 to 7.4	T1, T2 (relevant)
13	8 Multi-rate Digital Signal Processing 8.1 Introduction 8.2 Decimation by a Factor D 8.3 Interpolation by a Factor I	8.1 to 8.3	T1, T2 (relevant)
14	8.4 Sampling Rate Conversion by a Rational Factor I/D 8.5 Implementation of Sampling Rate Conversion	8.4 to 8.5	T1, T2 (relevant)
15	9 DSP Architectures 9.1 Generic Structure 9.2 ALU, AGU, MAC, Barrel Shifter units		R3
16	End-sem review session

Detailed Plan for Live MATLAB Demonstrations work (done by the faculty in the class with real time interpretation). These are the sample examples of the text book which are demonstrated in live on MATLAB to get a feel of the steps in the Algorithms.

Lab No	Objective	Content Reference
1	Types of Convolutions : Linear, Circular, Block Convolution(Overlap Add, Overlad Save Method)	MATLAB
2	DIT & DIF FFT	MATLAB
3	Split Radix FFT	MATLAB
4	DCT, IDCT	MATLAB
5	Analog IIR filter design {Butterworth, Chebyshev}	MATLAB

Work integration: Detailed plan

No	Activity description
1	Discuss Student's work experience with relevant topics and correlate with the theory.

Project work: None

Evaluation Scheme:  

Legend: EC = Evaluation Component; AN = After Noon Session; FN = Fore Noon Session

No	Name	Type	Duration	Weight	Day, Date, Session, Time
EC-1	Quiz-I	Online	-	5%	August 26 to September 4, 2017
	Assignment-I			5%	September 26 to October 4, 2017
	Assignment-II			10%	October 20 to 30, 2017
EC-2	Mid-Semester Test	Closed Book	2 hours	30%	24/09/2017 (AN) 2 PM – 4 PM
EC-3	Comprehensive Exam	Open Book	3 hours	50%	05/11/2017 (AN) 2 PM – 5 PM

 Note: If Assignment kindly remove Quiz-I, II, III

Syllabus for Mid-Semester Test (Closed Book): Topics in Session Nos.  1 to 8

Syllabus for Comprehensive Exam (Open Book): All topics (Session Nos. 1 to 16)

Important links and information:

Elearn portal: https://elearn.bits-pilani.ac.in

Students are expected to visit the Elearn portal on a regular basis and stay up to date with the latest announcements and deadlines.

Contact sessions: Students should attend the online lectures as per the schedule provided on the Elearn portal.

Evaluation Guidelines:

1.       EC-1 consists of either two Assignments or three Quizzes. Students will attempt them through the course pages on the Elearn portal. Announcements will be made on the portal, in a timely manner.

2.       For Closed Book tests: No books or reference material of any kind will be permitted.

3.       For Open Book exams: Use of books and any printed / written reference material (filed or bound) is permitted. However, loose sheets of paper will not be allowed. Use of calculators is permitted in all exams. Laptops/Mobiles of any kind are not allowed. Exchange of any material is not allowed.

4.       If a student is unable to appear for the Regular Test/Exam due to genuine exigencies, the student should follow the procedure to apply for the Make-Up Test/Exam which will be made available on the Elearn portal. The Make-Up Test/Exam will be conducted only at selected exam centres on the dates to be announced later.

It shall be the responsibility of the individual student to be regular in maintaining the self study schedule as given in the course handout, attend the online lectures, and take all the prescribed evaluation components such as Assignment/Quiz, Mid-Semester Test and Comprehensive Exam according to the evaluation scheme provided in the handout.