Statistical Signal Processing - Detection, Estimation, and Time Series Analysis;[Louis Scharf];统计信号处理里面的经典书籍;

小波分析的经典教材，外文的，有兴趣的可以下来看看

《Synthetic Aperture Radar Signal Processing with MATLAB Algorithms》本书影印版pdf。

从工程师的应用角度来分析数字信号处理的脉络。同时又从科学家的研究角度来探索数字信号的潜力和发展方向。不同于教科书式的理论推导正确，意在启发读者从实用的角度来方向思考理论的模型。

数字信号处理——原理、算法与应用。国外电子与通信教材系列，方艳梅，刘永清 等译。Digital signal processing principles,algorithms,and applications 习题答案

Documentation for Matlab Toolbox

G. Manolakis 的Statistical and Adaptive Signal Processing，图书及Matlab代码。

CONTENT PART 1 BASICS OF INFERENCE OVER NETWORKS CHAPTER 1 Asynchronous Adaptive Networks CHAPTER 2 Estimation and Detection Over Adaptive Networks CHAPTER 3 Multitask Learning Over Adaptive Networks With Grouping CHAPTER 4 Bayesian Approach to Collaborative Inference in Networks CHAPTER 5 Multiagent Distributed Optimization CHAPTER 6 Distributed Kalman and Particle Filtering CHAPTER 7 Game Theoretic Learning PART 2 SIGNAL PROCESSING ON GRAPHS CHAPTER 8 Graph Signal Processing . CHAPTER 9Sampling and Recovery of Graph Signals CHAPTER 10 Bayesian Active learning on Graphs . CHAPTER 1 1 Design of Graph Filters and Filterbanks CHAPTER 12 Statistical Graph Signal Processing: Stationarity and Spectral Estimation CHAPTER 1 3 Inference of Graph Topology CHAPTER 14 Partially Absorbing Ranclom Walks: A Unifiecl Framework for Learning on Graphs PART 3 DISTRIBUTED COMMUNICATIONS, NETWORKING, AND SENSING . . . . .

信号处理估计理论经典书籍,fundamental of statistical signal processing estimation theory

Fundamentals of Statistical Signal Processing: Practical Algorithm Development is the third volume in a series of textbooks by the same name. Previous volumes described the underlying theory of estimation and detection algorithms. In contrast, the current volume addresses the practice of converting this theory into software algorithms that may be implemented on a digital computer. In describing the methodology and techniques, it will not be assumed that the reader has studied the first two volumes, but of course, he/she is certainly encouraged to do so. Instead, the descriptions will focus on the general concepts using a minimum of mathematics but will be amply illustrated using MATLAB implementations. It is envisioned that the current book will appeal to engineers and scientists in industry and academia who would like to solve statistical signal processing problems through design of well-performing and implementable algorithms for real systems.