Digital Signal Processing

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DIGITAL SIGNAL PROCESSING 2171003
FREE PDF 2171003
Code: 2171003 Credits: 6 Semester 7 EEE

Digital Signal Processing

Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.

Digital Signal Processing Syllabus — Unit-wise Content

The official GTU curriculum for Digital Signal Processing (subject code 2171003) as prescribed for EEE · Semester 7 divides the course into 8 units, covering 47 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.

Download the official syllabus PDF (2171003)

Unit 1 Introduction to DSP

3 lecture hours

  • Overview Signals
  • systems and signal processing
  • classification of signals
  • elements of digital signal processing system
  • concept of frequency in continuous and discrete time signals
  • Periodic Sampling
  • Frequency domain representation of sampling
  • Reconstructions of band limited signals from its samples

Unit 2 Discrete-Time Signals and Systems (Frequency Domain analysis)

5 lecture hours

  • Z-transform & Inverse z-transform
  • Linear convolution and its properties
  • Linear Constant Coefficient Difference equations
  • Frequency domain representation of Discrete-Time Signals & Systems
  • Representation of sequences by discrete time Fourier Transform
  • Properties of discrete time Fourier Transform, and correlation of signals
  • Fourier Transform Theorems

Unit 3 Analysis of Linear Time Invariant System

8 lecture hours

  • Analysis of LTI systems in time domain and stability considerations
  • Frequency response of LTI system
  • System functions for systems with linear constant-coefficient Difference equations
  • Freq. response of rational system functions relationship between magnitude & phase
  • All pass systems
  • inverse systems
  • Minimum/Maximum phase systems
  • systems with linear phase

Unit 4 Structures for Discrete Time Systems

7 lecture hours

  • Block Diagram and signal flow diagram representations of Linear Constant-Coefficient Difference equations
  • Basic Structures of IIR Systems
  • lattice and lattice-ladder structures
  • Transposed forms
  • Direct and cascade form Structures for FIR Systems
  • Linear Phase FIR structure
  • Effects of Co-efficient quantization

Unit 5 Filter Design Techniques

9 lecture hours

  • Design of Discrete-Time IIR filters from Continuous-Time filters Approximation by derivatives
  • Impulse invariance and Bilinear Transformation methods
  • Design of FIR filters by windowing techniques

Unit 6 Discrete-Fourier Transform & Fast Fourier Transform

9 lecture hours

  • Representation of Periodic sequences: The discrete Fourier Series and its Properties Fourier Transform of Periodic Signals
  • Sampling the Fourier Transform
  • The Discrete-Fourier Transform
  • Properties of DFT, Linear Convolution using DFT
  • FFT-Efficient Computation of DFT, Goertzel Algorithm
  • radix2 Decimation-in-Time and Decimation- in-Frequency FFT Algorithms

Unit 7 Advance DSP Techniques

7 lecture hours

  • Multirate Signal Processing: Decimation
  • Sampling rate conversion by rational factor Adaptive filters: Introduction
  • Basic principles of Forward Linear Predictive filter and applications such as system identification
  • echo cancellation
  • equalization of channels, and beam forming using block diagram representation study only

Unit 8 Architecture of DSP Processors & applications

4 lecture hours

  • Harward architecture
  • Multiplier-accumulator (MAC) hardware
  • architectures of fixed and floating point (TMSC6000) DSP processors

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