Toggle navigation sidebar

Toggle in-page Table of Contents

Topics in Signal Processing

Foundation

1. Algebra
2. Elementary Real Analysis
3. Metric Spaces
4. Linear Algebra
5. Multivariate Calculus
- 5.1. Differentiation
- 5.2. Differentiation in Banach Spaces
6. Geometry
- 6.1. Algebraic Geometry
7. Probability
8. Numerical Optimization
- 8.1. Mathematical Optimization

Convexity

9. Convex Sets and Functions
10. Convex Optimization
11. Subgradient Methods
- 11.1. Basic Subgradient Method
12. Proximal Algorithms
- 12.3. Proximal Mappings and Operators

Signal Processing

13. Signal Theory
14. Detection and Estimation Theory
15. Coding Theory
16. Wavelets

Machine Learning

17. Data Clustering

Sparsity

18. Sparse Signal Models
19. Compressive Sensing
- 19.1. Sensing Matrices
- 19.2. Quantization
20. Sparse Approximation with Dictionaries
21. Sparse Recovery from Compressive Measurements
22. Dictionary Learning
- 22.1. Introduction

Applications

23. Subspace Clustering
- 23.5. Motion Segmentation

Epilogue

Notation
Bibliographic Notes
Index

Powered by Jupyter Book

repository
open issue
suggest edit

.md

Metric Spaces

3. Metric Spaces#

Chapter objectives

Metric spaces

previous

2.8. Some Important Inequalities

next

3.1. Introduction

By Shailesh Kumar
© Copyright 2021-2022.