Unit 1 Introduction

6 lecture hours

• 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
• sampling low pass signals
• sampling bandpass signals
• spectral inversion in bandpass sampling
• general applications of DSP

Unit 2 Discrete-Time Signals and Systems

5 lecture hours

• Discrete-Time Signals
• Discrete-Time Systems
• LTI Systems
• Properties of LTI Systems
• linear convolution and its properties
• Linear Constant Coefficient Difference equations

Unit 3 The Z- Transform and its Application in to Analysis of LTI System

6 lecture hours

• Properties Z-transform
• Rational Z-transform
• the inverse Z-transform methods
• Analysis of LTI systems in Z domain

Unit 4 Discrete-Fourier Transform and Fast Fourier Transform

8 lecture hours

• Discrete Fourier transform and its properties
• Inverse DFT, Fourier Transform of Periodic Signals
• Linear Convolution using DFT, efficient computation of DFT:FFT
• Frequency analysis of continues and discrete time signal
• Properties of discrete time Fourier Transform, and correlation of signals
• Fourier Transform Theorem

Unit 5 Filter Design Techniques

7 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
• Illustrative design examples of IIR and filters

Unit 6 Signal Processing Techniques for Mechatronics Engineers

• Envelope Analysis
• Adaptive Filters
• Introduction of random signal
• Correlation functions
• 07 Subject Code: 3724707 w.e.f