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说明：  matlab仿真生成C/A码　,希望大家可以用的上，能帮上忙，谢谢(GPS　signal C/A code generation,use matlab similution,very useful,hope you will like ,thank you,enjoy it)

说明：  针对Z变换法无法求取相邻采样点之间的输出响应的局限，利用MATLAB程 序语言，对单位负反馈系统的改进z变换法进行了程序设计。通过simulink仿真的实验，证 明该程序运算快速、准确，使用方便。(For the Z transform method can not strike between adjacent sampling points in response to the limitations of the output, using MATLAB programming language, a negative feedback system of units of the z transform method to improve the program design. Through simulink simulation experiments show that the procedures for computing fast, accurate and easy to use.)

说明：  一种快速有效、性能可靠的信号重构算法是压缩感知理论的核心部分，对于 这部分内容，许多卓有成效的研究工作正在陆续展开。从压缩感知理论提出至今， 已经出现了多种稀疏信号的重构算法。重构算法主要可以归结为三大类：贪婪算 法，凸松弛算法和组合算法。这里主要是SP算法(A fast and efficient, reliable signal reconstruction algorithm is the core of compressed sensing theory, for this part, much fruitful research work is carried out successively. From the compressed sensing theory so far, there have been many sparse signal reconstruction algorithm. Reconstruction algorithm can be summarized into three main categories: the greedy algorithm, convex relaxation algorithms and combinatorial algorithms. This algorithm is mainly SP)

On a map, place a label corresponding to any of the 25,394 features identified by SCAR.

程序实现了naive bayes classifier， 并附有对美国参议院根据投票情况来判断议员属于民主党还是共和党的例子。(Program achieved a naive bayes classifier, along with the U.S. Senate voting to determine under Democrat and Republican members belonging examples.)

photovoltaic array simulation matlab

nelder-mead算法,程序不算太长，应该好理解，仔细看几遍就行了(nelder-mead method， it is very useful if you want it,just download it!)

匹配追踪和正交匹配追踪，包含收发两个客户端程序，连续相位调制信号(CPM)产生。( Matching Pursuit and orthogonal matching pursuit, Transceiver contains two client programs, Continuous phase modulation signal (CPM) to produce.)

matlab下可以直接使用的小程序 包括各种常用算法 对应书籍为《matlab宝典》 此为总的部分(matlab can be directly used for small programs include a variety of commonly used algorithms corresponding books as " matlab book" This is part of the total)

展示了线性、DFE、MLSE均衡器的信噪比性能，并通过蒙特卡罗模拟信道估计结果确定。(This demo shows the BER performance of linear, decision feedback (DFE), and maximum likelihood sequence estimation (MLSE) equalizers when operating in a static channel with a deep null. The MLSE equalizer is invoked first with perfect channel knowledge, then with an imperfect, although straightforward, channel estimation algorithm. The BER results are determined through Monte Carlo simulation. The demo shows how to use these equalizers seamlessly across multiple blocks of data, where equalizer state must be maintained between data blocks. )