BPSK_Simulation

简单蚁群算法求解TSP的matlab源程序(simple ant algorithm for TSP source of Matlab)

麦克风阵 ＋ 波束形成 后Wiene滤波 (Microphone array+ beamforming after Wiene filtering)

说明：  高等光学仿真（matlab版）-光波导、激光书中部分程序(Higher optical simulation (matlab)- waveguide, the laser part of the program in the book)

Frequency-resolved optical gating

rls s matlab Simulation Program

翻译了3GPP 25213-700扩频部分的协议内容,此标准翻译的还算标准,可以直接使用(translated 3GPP 25213-700 spreading part of the agreement, Such standards are fairly standard translation can be used directly)

CMA WITH N EQUAL TO 8,4,20

实际应用matlab程序解决方程的LU分解问题，为顺序消元法(Matlab program to solve the practical application of the LU decomposition equation for the sequential elimination method)

In computer science and information theory, data compression, source coding,[1] or bit-rate reduction involves encoding information using fewer bits than the original representation. Compression can be either be lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by identifying marginally important information and removing it. The process of reducing the size of a data file is popularly referred to as data compression, although its formal name is source coding (coding done at the source of the data, before it is stored or transmitted).

Compressive sampling is an emerging technique that promises to effectively recover a sparse signal from far fewer measurements than its dimension. The compressive sampling theory assures almost an exact recovery of a sparse signal if the signal is sensed randomly where the number of the measurements taken is proportional to the sparsity level and a log factor of the signal dimension. Encouraged by this emerging technique, this thesis briefly reviews the application of Compressive sampling in speech processing. It comprises the basic study of two necessary condition of compressive sensing theory: sparsity and incoherence. In this thesis, various sparsity domain and sensing matrix for speech signal and different pairs that satisfy incoherence condition has been compiled.