This textbook introduces sparse and redundant representations with a focus on applications in signal and image processing. The theoretical and numerical foundations are tackled before the applications are discussed. Mathematical modeling for signal sources is discussed along with how to use the proper model for tasks such as denoising, restoration, separation, interpolation and extrapolation, compression, sampling, analysis and synthesis, detection, recognition, and more. The presentation is elegant and engaging. Sparse and Redundant Representations is intended for graduate students in applied mathematics and electrical engineering, as well as applied mathematicians, engineers, and researchers who are active in the fields of signal and image processing.

很好的一本关于傅立叶变换的课本，适合通讯，电子，物理电子等相关专业学生，当然了，是英文版的，需要硬着头皮看了。

心音-深度学习 该项目旨在在低功耗ARM处理器（例如在树莓派上找到的处理器）上运行。 目的是将该软件打包到一个小型硬件设备中，发展中国家的护理工作者可以使用该设备来检测心脏病的早期发作。

With continuing progress in VLSI and ASIC technologies, digital signal processing (DSP) algorithms have continued to find great use in increasingly wide application areas. DSP has gained popularity also in embedded systems although these systems set challenging constraints for implementations. Embedded systems contain limited resources, thus embedded DSP systems must balance tradeoffs between the requirements on computational power and computational resources. Energy efficiency has been important in batterypowered devices, but nowadays also the limited heat dissipation in small devices calls for low-power consumption. Successful implementation of DSP applications in embedded systems requires tailoring, which in turn sets challenges for design methodologies.

Probability and Random Processes with Application to Signal Processing，经典的信号处理教程，英文原版，非扫描版，带部分书签

Real-Time Digital Signal Processing from MATLAB to C with the TMS320C6x DSPs 3rd 第三版 矢量pdf 非扫描

频率域低通滤波matlab代码 使用加窗傅立叶变换研究低通音频滤波器和信号处理 该项目使用多种类型的窗口傅立叶变换来研究时频域中的音乐样本。 我特别研究了这种变换的调谐，以及海森堡不确定性对时间和频率分辨率的限制。 我还执行泛音过滤并研究不同窗口类型对这项任务的功效。 是对项目的介绍，包括可视化、方法和背景。 动机 该项目最初是为了满足华盛顿大学应用数学项目数据科学和科学计算研究生课程的任务。 框架 -MATLAB 2019 图例 代码示例 %% Build the time and frequency domains L = length(v)/Fs; n = length(v); t2 = linspace(0, L, n+1); t = t2(1:n); k = (2*pi/L)*[0:n/2-1 -n/2:-1]; ks = fftshift(k); v = v(1:end - 1); v_t = fft(v); %% Plot in freq. domain of original file close all plot(ks,abs(fftshift(v_t))/max(a

Fourier transforms are used everyday for solving single functions and combinations of functions found in radar and signal processing. Still, many problems that could have been solved by using Fourier transforms have gone unsolved because they require integration that is too computationally difficult. This manual demonstrates how you can solve those integration-intensive problems with an approach to carrying out Fourier transforms. By building upon Woodward's well-known "Rules and Pairs" method and related concepts and procedures, the text establishes a unified system that makes implicit the integration required for performing Fourier transforms on a wide variety of functions. It details how complex functions can be broken down to their constituent parts for analysis. This approach to applying Fourier transforms is illustrated with many specific examples from digital signal processing as well as radar and antenna operation.

Real-Time Digital Signal Processing, 2nd Edition by Sen Maw, Kuo本版是完整版.原來網上的不全.

目前图信号处理是最火的研究热点之一。这里是图信号处理中的滤波操作。（graph signal processing：filtering.）