EE8591 Digital Signal Processing Lecture Notes

Anna University, Chennai
Department of Electrical and Electronics Engineering

Subject Code: EE8591
Subject Name: Digital Signal Processing

Lecture Notes - All Units

Unit 1: Introduction to Digital Signal Processing (DSP)

1.1 Overview of Digital Signal Processing

Introduction to Signals and Systems
Analog vs. Digital Signal Processing
Applications of DSP in Communication, Audio Processing, Image Processing, and Control Systems
1.2 Discrete-Time Signals and Systems

Discrete-Time Signals: Definition, Classification, and Representation
Discrete-Time Systems: Classification, Properties, and Operations
Convolution Sum and Difference Equations
1.3 Sampling and Quantization

Sampling Theorem and Nyquist Rate
Aliasing and Anti-aliasing Filters
Quantization: Uniform and Non-uniform Quantization, Quantization Error
Unit 2: Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT)

2.1 Discrete Fourier Transform (DFT)

Definition and Properties of DFT
DFT Computation: Direct Computation, FFT Algorithms
Properties of DFT: Linearity, Time Shifting, Time Reversal, Time Scaling, Convolution Theorem
2.2 Fast Fourier Transform (FFT)

Introduction to FFT Algorithms: Radix-2 FFT, Radix-4 FFT
FFT Implementation: Decimation-in-Time (DIT) and Decimation-in-Frequency (DIF) Algorithms
Applications of FFT in Spectrum Analysis, Filtering, and Modulation Techniques
Unit 3: Z-Transform and Digital Filter Design

3.1 Z-Transform

Definition and Properties of Z-Transform
Region of Convergence (ROC) and Inverse Z-Transform
Properties of Z-Transform: Linearity, Time Shifting, Time Reversal, Time Scaling, Convolution Theorem
3.2 Digital Filter Design

FIR Filter Design: Windowing Techniques, Frequency Sampling Method
IIR Filter Design: Butterworth, Chebyshev, and Elliptic Filters
Design of Digital Filters using MATLAB and Signal Processing Toolboxes
Unit 4: Finite Word Length Effects and Quantization

4.1 Finite Word Length Effects

Fixed-Point and Floating-Point Representations
Quantization Error and Round-off Noise
Analysis of Quantization Effects in DSP Systems
4.2 Quantization Techniques

Quantization Schemes: Uniform, Non-uniform, Mid-tread, Mid-rise Quantization
Quantization Error Analysis and Signal-to-Noise Ratio (SNR) Calculation
Optimization Techniques for Minimizing Quantization Error
Unit 5: Digital Signal Processing Applications

5.1 Speech and Audio Signal Processing

Speech Signal Analysis: Short-Time Fourier Transform (STFT), LPC Analysis
Speech Compression Techniques: Adaptive Differential Pulse Code Modulation (ADPCM), Speech Coding Standards (e.g., GSM, G.711)
5.2 Image Processing

Image Representation and Enhancement Techniques
Image Compression: Discrete Cosine Transform (DCT), JPEG Compression
Image Filtering and Restoration: Median Filtering, Wiener Filtering
5.3 Biomedical Signal Processing

ECG Signal Processing: QRS Detection, Heart Rate Variability Analysis
EEG Signal Processing: Frequency Analysis, Event-related Potentials
Signal Processing Techniques for Medical Imaging (MRI, CT, Ultrasound)
These lecture notes provide comprehensive coverage of Digital Signal Processing (DSP), tailored for students in the Department of Electrical and Electronics Engineering at Anna University, Chennai. With a total of 61 pages in PDF format, these notes include detailed explanations, mathematical derivations, practical examples, and MATLAB demonstrations to facilitate understanding and application. Students will gain proficiency in the fundamental concepts of DSP, Fourier analysis, digital filter design, finite word length effects, and various applications of DSP in communication, audio processing, image processing, and biomedical signal processing.

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    EE8591 Digital Signal Processing Lecture Notes