Digital Signal Processing Handbook 1st editon by Vijay Madisetti ISBN 0849385725 978-0849385728

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ISBN 10: 0849385725
ISBN 13: 978-0849385728
Author: Vijay Madisetti

The field of digital signal processing (DSP) has spurred developments from basic theory of discrete-time signals and processing tools to diverse applications in telecommunications, speech and acoustics, radar, and video. This volume provides an accessible reference, offering theoretical and practical information to the audience of DSP users.

This immense compilation outlines both introductory and specialized aspects of information-bearing signals in digital form, creating a resource relevant to the expanding needs of the engineering community. It also explores the use of computers and special-purpose digital hardware in extracting information or transforming signals in advantageous ways.

Digital Signal Processing Handbook 1st Table of contents:

Chapter 1: Introduction to Digital Signal Processing
1.1. Overview of Signal Processing
1.2. Digital vs. Analog Signal Processing
1.3. The Role of DSP in Modern Technology
1.4. Basic Components of DSP Systems
1.5. The DSP Workflow: Sampling, Quantization, and Processing
1.6. Applications of Digital Signal Processing

Chapter 2: Mathematical Foundations of DSP
2.1. Signals and Systems: Definitions and Properties
2.2. Time-Domain and Frequency-Domain Representations
2.3. Fourier Series and Fourier Transform
2.4. Discrete-Time Signals and Systems
2.5. Z-Transform and its Applications
2.6. Convolution and Correlation

Chapter 3: Discrete-Time Signals and Systems
3.1. Representation of Discrete-Time Signals
3.2. Linear Time-Invariant Systems
3.3. System Response and Convolution
3.4. Stability and Causality
3.5. Discrete-Time Fourier Transform (DTFT)
3.6. Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT)

Chapter 4: Digital Filter Design
4.1. Introduction to Digital Filters
4.2. Filter Specifications and Characteristics
4.3. Types of Digital Filters: FIR and IIR Filters
4.4. Filter Design Methods: Windowing, Bilinear Transform, and Frequency Sampling
4.5. FIR Filter Design
4.6. IIR Filter Design
4.7. Filter Realization: Direct and Cascade Forms

Chapter 5: Spectral Analysis
5.1. Spectral Representation of Signals
5.2. Power Spectral Density (PSD)
5.3. Periodogram and Bartlett’s Method
5.4. Welch’s Method for Power Spectral Estimation
5.5. Time-Frequency Analysis: Short-Time Fourier Transform (STFT)
5.6. Wavelet Transform and Its Applications

Chapter 6: Signal Sampling and Quantization
6.1. The Sampling Theorem
6.2. Aliasing and Anti-Aliasing Filters
6.3. Quantization and Quantization Noise
6.4. Uniform and Non-Uniform Quantization
6.5. Bit Depth and Signal Resolution
6.6. Sampled Data Processing

Chapter 7: Advanced Filter Design and Applications
7.1. Adaptive Filters
7.2. Least Squares and LMS Algorithms
7.3. Kalman Filters
7.4. Wiener Filters
7.5. Digital Equalization
7.6. Applications of Adaptive Filtering

Chapter 8: Time and Frequency Domain Techniques
8.1. Time-Domain Signal Processing
8.2. Frequency-Domain Signal Processing
8.3. Filtering in the Frequency Domain
8.4. Time-Frequency Domain Applications
8.5. Multirate Signal Processing
8.6. Decimation and Interpolation

Chapter 9: Multidimensional Signal Processing
9.1. Two-Dimensional Discrete Signals
9.2. Two-Dimensional DFT
9.3. Image Processing and Enhancement
9.4. Multidimensional Filtering
9.5. Video Signal Processing
9.6. Applications of Multidimensional DSP

Chapter 10: DSP in Communications
10.1. Modulation and Demodulation Techniques
10.2. Signal Detection and Estimation
10.3. Equalization Techniques
10.4. Error Control Coding
10.5. Speech and Audio Signal Processing
10.6. Channel Estimation and Equalization

Chapter 11: DSP in Audio and Speech Processing
11.1. Audio Signal Representation
11.2. Speech Coding and Compression
11.3. Speech Recognition
11.4. Noise Reduction Techniques
11.5. Audio Effects and Processing
11.6. Music Signal Processing

Chapter 12: DSP in Image and Video Processing
12.1. Image Representation and Compression
12.2. Image Enhancement and Restoration
12.3. Edge Detection and Feature Extraction
12.4. Video Signal Processing
12.5. Motion Estimation and Compensation
12.6. Applications in Computer Vision

Chapter 13: Real-Time DSP Systems
13.1. Real-Time Constraints and Systems
13.2. DSP Hardware: Processors and Accelerators
13.3. Programming for Real-Time DSP Systems
13.4. Embedded Systems in DSP
13.5. Design of Real-Time DSP Applications
13.6. Case Studies of Real-Time DSP Systems

Chapter 14: DSP Applications in Control Systems
14.1. DSP in Control System Design
14.2. Digital Controllers and Algorithms
14.3. Real-Time Control Using DSP
14.4. System Identification and Model Predictive Control
14.5. DSP in Robotics and Automation
14.6. Applications in Industrial Control Systems

Chapter 15: Future Trends in Digital Signal Processing
15.1. Machine Learning and DSP Integration
15.2. DSP in 5G and Beyond Wireless Networks
15.3. IoT and DSP Technologies
15.4. Quantum Computing and Signal Processing
15.5. Artificial Intelligence in DSP
15.6. Emerging Applications of DSP in Healthcare and Medicine

Appendices
A.1. Glossary of Terms
A.2. DSP Software and Tools
A.3. Key Algorithms and Formulas
A.4. Further Reading and References
A.5. Index

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