Book Details
EN
فا
Fundamentals of Graph Signal Processing
Table of Contents
Chapter 1: Introduction to Graph Theory
Chapter 2: Graph Signals and Filtering
Chapter 3: Graph Fourier Transform
Chapter 4: Graph Wavelets
Chapter 5: Applications in Machine Learning
Chapter 6: Network Analysis
Chapter 7: Case Studies
Key Features
- •Comprehensive coverage of graph signal processing fundamentals
- •Practical examples with MATLAB code
- •Over 120 illustrations and diagrams
- •End-of-chapter exercises with solutions
- •Real-world applications in network analysis
- •Advanced topics in graph neural networks
Additional Resources
The book comes with supplementary materials including:
- MATLAB code examples
- Dataset references
- Additional exercises
- Lecture slides for instructors