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Syllabus | B. Tech. Electronics & Communication Engineering | Digital Signal Processing

13040406 Digital Signal Processing L T P C
Version1.1 Date of Approval: Jun 06, 2013 3 0 0 3
Pre-requisites//Exposure  Signals and Systems
co-requisites  

 

Course Objectives

  1. To impart the knowledge of key DSP concepts and how do they relate to real applications.
  2. To introduce to the methods of time domain and frequency domain implementation.
  3. To present a comprehensive introduction to important DSP technologies with a focus on filter design techniques and Fourier analysis of signals using DFT.

Course Outcomes

On completion of this course, the students will be able to

  1. Apply digital signal processing fundamentals.
  2. Acquire the knowledge of representation of discrete-time signals in the frequency domain, using z-transform and discrete Fourier transform.
  3. Learn the basic forms of FIR and IIR filters, and how to design filters with desired frequency responses.
  4. To construct new experiment independently or as a team member.

Catalog Description

Digital signal processing (DSP) is concerned with the representation of signals in digital form, and with the processing of these signals and the information that they carry. Although DSP, as we know it today, began to flourish in the 1960’s, some of the important and powerful processing techniques that are in use today may be traced back to numerical algorithms that were proposed and studied centuries ago. Since the early 1970’s, when the first DSP chips were introduced, the field of digital signal processing has evolved dramatically. With a tremendously rapid increase in the speed of DSP processors, along with a corresponding increase in their sophistication and computational power,digital signal processing has become an integral part of many commercial products and applications, and is becoming a commonplace term.

Text Books

  1. Oppenheim A.V., Schafer, Ronald W. & Buck, John R.,”Discrete Time Signal processing”, Pearson Education ,2nd Edition. 

Reference Books

  1. De Fatta, D.J.Lucas, J.G. & Hodgkiss, W. S.,” Digital Signal Processing”, John Wiley& Sons.
  2. Proakis, J.G. & Manolakis, D.G.,” Digital Signal Processing: Principles Algorithms and Applications”, Prentice Hall of India.
  3. Rabiner, L.R. and Gold B., “Theory and applications of DSP”, Prentice Hall of India.

Course Content 

Unit I: Discrete Time Signals and Systems                                     6 lecture hours

6 lecture hours

Sequences, discrete time systems, LTI systems, frequency domain representation of discrete time signals and systems, discrete time signals and frequency domain representation, Fourier Transform Discrete Fourier Transform: Discrete Fourier transforms, properties, linear convolution using DFT, DCT.

Unit II: Sampling of Continuous Time Signals                              8 lecture hours

8 lecture hours

Sampling and reconstruction of signals, frequency domain representation of sampling, discrete time processing of continuous time signals, continuous time processing of discrete time signals, changing the sampling rate using discrete time processing, multi rate signal processing, digital processing of analog signals, over sampling and noise shaping in A/D and D/A conversion. 

Unit III: Transform Analysis of LTI Systems                               

9 lecture hours

Frequency response of LTI systems, system functions, frequency response for rational system functions, magnitude-phase relationship, all pass systems, minimum phase systems, and linear systems with generalized linear phase Overview of finite precision numerical effects, effects of coefficient quantization, Effects of round-off noise in digital filters, zero-input limit cycles in fixed point realizations of IIR digital filters.

Unit IV : Filter Design Techniques                                                

7 lecture hours

Design of D-T IIR filters from continuous – time filters, design of FIR filters by windowing, Kaiser Window method, optimum approximations of FIR filters, FIR equiripple approximation.

Unit V: Fourier Analysis of Signals Using DFT                  

9 lecture hours

DFT analysis of sinusoidal signals, time-dependent Fourier transforms: Block convolution, Fourier analysis of non – stationary and stationary random signals, spectrum analysis of random signals using estimates of the autocorrelation sequence. 

Mode of Evaluation: The theory and lab performance of students are evaluated separately. 

  Theory Laboratory Theory and laboratory
Components Internal SEE Internal SEE
Marks 50 50 50 50
Total Marks 100 100
Scaled Marks 75 25 100

Relationship between the Course Outcomes (COs) and Program Outcomes (POs)

Mapping between Cos and Pos
Sl. No. Course Outcomes (COs) Mapped Programme Outcomes
1 apply digital signal processing fundamentals.

.

2
2 acquire the knowledge of representation of discrete-time signals in the frequency domain, using z transform and discrete Fourier transform.

 

5
3 Learn the basic forms of FIR and IIR filters, and how to design filters with desired frequency responses.

 

3
4 To construct new experiment independently or as a team member. 9

 

    Engineering Knowledge Problem analysis Design/development of solutions Conduct investigations of complex problems Modern tool usage The engineer and society Environment and sustainability Ethics Individual or team work Communication Project management and finance Life-long Learning
    1 2 3 4 5 6 7 8 9 10 11 12
TEC222 Digital Signal Processing   2 3   2       2      

1=addressed to small extent

2= addressed significantly

3=major part of course

 

Theory  The theory of this course is used to evaluate the program outcome PO(3)
  Lab  The laboratory of this course is used to evaluate the program outcome PO(9)
ADMISSIONS 2021