http://www.dspguide.com/pdfbook.htm FOUNDATIONS Chapter 1 - The Breadth and Depth of DSP The Roots of DSP Telecommunications Audio Processing Echo Location Image Processing Chapter 2 - Statistics, Probability and Noise Signal and Graph Terminology Mean and Standard Deviation Signal vs. Underlying Process The Histogram, Pmf and Pdf The Normal Distribution Digital Noise Generation Precision and Accuracy Chapter 3 - ADC and DAC Quantization The Sampling Theorem Digital-to-Analog Conversion Analog Filters for Data Conversion Selecting The Antialias Filter Multirate Data Conversion Single Bit Data Conversion Chapter 4 - DSP Software Computer Numbers Fixed Point (Integers) Floating Point (Real Numbers) Number Precision Execution Speed: Program Language Execution Speed: Hardware Execution Speed: Programming Tips FUNDAMENTALS Chapter 5 - Linear Systems Signals and Systems Requirements for Linearity Static Linearity and Sinusoidal Fidelity Examples of Linear and Nonlinear Systems Special Properties of Linearity Superposition: the Foundation of DSP Common Decompositions Alternatives to Linearity Chapter 6 - Convolution The Delta Function and Impulse Response Convolution The Input Side Algorithm The Output Side Algorithm The Sum of Weighted Inputs Chapter 7 - Properties of Convolution Common Impulse Responses Mathematical Properties Correlation Speed Chapter 8 - The Discrete Fourier Transform The Family of Fourier Transform Notation and Format of the Real DFT The Frequency Domain's Independent Variable DFT Basis Functions Synthesis, Calculating the Inverse DFT Analysis, Calculating the DFT Duality Polar Notation Polar Nuisances Chapter 9 - Applications of the DFT Spectral Analysis of Signals Frequency Response of Systems Convolution via the Frequency Domain Chapter 10 - Fourier Transform Properties Linearity of the Fourier Transform Characteristics of the Phase Periodic Nature of the DFT Compression and Expansion, Multirate methods Multiplying Signals (Amplitude Modulation)

提出实用技术中的数字信号处理，同时避免了详尽的数学和抽象理论的障碍。

国外大牛所著，从基础入手，详细阐述了阵列信号的特性，并从工程角度描述了多种自适应阵列信号处理算法，DOA估计等技术，帮助读者快速进入阵列信号处理领域

别的网站找到的中文版。Fundamentals of Statistical Signal Processing: Estimation Theory

作者Seven.Kay，国外检测原理课程教材；现代检测理论top教材

图像处理基础（英文第2版）。从数学的角度去看图像处理技术，非常值得一读。作者：Maria Petrou Costas Petrou，是英国帝国理工的大牛。

processing 软件入门指导书 英文版主要讲ai的实现

Subspace global skyline query processing

这本免费书籍重点介绍MapReduce算法设计，重点介绍自然语言处理，信息检索和机器学习中常见的文本处理算法。

BioSPPy-Python中的生物信号处理 用Python编写的用于生物信号处理的工具箱。 该工具箱将各种信号处理和模式识别方法捆绑在一起，旨在进行生物信号分析。 强调： 支持各种生物信号：PPG，ECG，EDA，EEG，EMG，呼吸 信号分析原语：滤波，频率分析 聚类 生物识别 可以在以下位置找到文档： : 安装 使用pip可以轻松完成安装： $ pip install biosppy 简单的例子 下面的代码从examples文件夹中加载ECG信号，对其进行过滤，执行R峰检测并计算瞬时心率。 from biosppy import storage from biosppy . signals import ecg # load raw ECG signal signal , mdata = storage . load_txt ( './examples/ecg.txt'