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

13040515 Advanced Signal Processing L T P C
Version1.0 Date of Approval: — 3 1 0 3
Pre-requisites//Exposure Signal & System

Course Objectives

  1. Students learn the essential advanced topics in digital signal processing that are necessary for successful graduate-level research.
  2. The course includes a review of the linear constant-coefficient system properties covered in an undergraduate DSP course, and then examines a variety of multirate filter structures, time-varying and adaptive systems, fast algorithms, and other topics relevant to the research areas of the students. 

Course Outcomes

On completion of this course, you should be able to:

  1. Master modern signal processing tools including vector spaces, bases and frames, operators, signal expansions and approximation, as well as classical signal processing tools including Fourier and z transforms, filtering, and sampling.
  2. Apply the above tools to real-world problems including spectral analysis, filter design, noise cancellation, signal compression, rate conversion, feature extraction, inverse problems, machine learning and justify why these are appropriate tools.
  3. Think critically, ask questions, and apply problem-solving techniques to homework and midterm exams.
  4. Research, present, and report on a selected topic that is of current interest within a specified time.

Catalog Description 

Basic concept review of digital signals and systems; computer-aided digital filter design, quantization effects, decimation and interpolation, and fast algorithms for convolution and the DFT; introduction to adaptive signal processing.

Text Books

  1. “Digital Signal Processing, 4th Edition” by Proakis and Manolakis, Prentice Hall, 2007 (ISBN: 0-13-187374-1).
  2. Vetterli, J. Kovacevic, and V. K. Goyal, “Foundation of Signal Processing”, Cambridge University Press, 2014

Reference Books

  1. Rabiner & Gold, “Theory & application of digital Signal Processing”, PHI 1992.
  2. Roman kuc, “Introduction to Digital Signal Processing,” McGraw hill Edition.
  3. Openheim AV & Schafer RW, Discrete Time Signal Processing PHI. 

Course Content

Unit I: Introduction of DSP                                                                                                  

8 lecture hours

Introduction to Signal Processing, Discrete Linear Systems, superposition Principle, Unit-Sample response, stability & causality Criterion.

Unit II: Fourier Transform & inverse Fourier transform

12 lecture hours

Fourier Transform & inverse Fourier transform: Frequency domain design of digital filters, Fourier transform, use of Fourier transform in Signal processing. The inverse fourier transform, Sampling continuous function to generate a sequence, Reconstruction of continuous -time signals from Discrete-time sequences.

Unit III: DFT & FFT & Z transform with Applications

14 lecture hours

Discrete Fourier transforms, properties of DFT, Circular Convolution, Fast Fourier Transform, and Realizations of DFT. The Z-transform, the system function of a digital filter, Digital Filter implementation from the system function, the inverse Z- transform, properties & applications, Special computation of finite sequences, sequence of infinite length & continuous time signals, computation of fourier series & time sequences from spectra.

Unit IV: Digital Filter Structure & Implementation                                            

14 lecture hours

Linearity, time invariance & causality, the discrete convolution, the transfer function, stability tests, steady state response, Amplitude & Phase characteristics, stabilization procedure, Ideal LP Filter, Physical reliability & specifications.FIR Filters, Truncation windowing & Delays, design example, IIR Filters: Review of design of analog filters & analog frequency transformation. Digital frequency transformation. Design of LP filters using impulse invariance method, Bilinear transformation, Phase equalizer, digital all pass filters.                                             

Unit V: Implementation of Filters                                                                                    

6 lecture hours

Realization block diagrams, Cascade & parallel realization, effect of infinite-word length, transfer function of degree 1&2, Sensitivity comparisons, effects of finite precision arithmetic on Digital filters. 

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