shiyan_2

解决2004年数学建模第一问求出力机组的源码(In 2004, the solution of mathematical modeling for output unit ask source)

example for national instruments devices

粒子群算法的matlab源代码，绝对可用！(Particle swarm optimization algorithm source code, absolutely free!)

本文基于MATLAB/SIMULINK动态仿真环境，以实例阐述了建立脉冲编码调制通信系统仿真模型的一般方法。根据该系统的基本原理将整个模型划分为抽样﹑量化﹑编码等几个子系统，并在传输线路上加入高斯白噪声以检验该系统的传输质量和抗干扰能力。(Title Design and Simulation for PCM communication system Abstract )

生成一系列X-Y多项式的程序，当你输入K值时，可以生成K（K-1）/2个基函数。可以直接调用(Generates a series of x-y polynomial program, when you enter K value, can generate K (K- 1)/2 basis functions.You can directly call)

说明：  多种群遗传优化算法，包括移民算子、人工选择算子以及标准遗传算法的代码(A variety of genetic optimization algorithms, including migration operator, manual selection operator and standard genetic algorithm code)

This M Code simulate the effects of clipping and filtering on PAPR PAPR reduction in OFDM-based wireless standard.Also the performance of BER versus SNR of original OFDM signals with PAPR reduction based on clipping and filtering schemes over AWGN channel is evaluated. The simplest and most widely used technique of PAPR reduction is to basically clip the part of signals that are outside the allowed region.Clipping methode introduces both in band distortion and out of band radiation into OFDM signals which degrades the performance including the BER and spectral efficiency.Filtering can reduce out of band radiation after clipping although it can not reduce in-band radiation distortion.However, clipping may cause some peak regrowth so that the signal after clipping and filtering will exceed the clipping level at some point.To reduce peak regrowth a repeated filtering and clipping operation can be used to obtain a desirable PAPR at a cost of computational complexity increase.

一个用Mathmatica编写的动画演示程序(with an animation prepared by the Mathmatica Demonstration Program)

MUSIC算法[1]是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成。(MUSIC algorithm [1] is a feature space based on matrix decomposition method. From the geometric point of view, the signal processing can be decomposed observation space the signal subspace and the noise subspace, it is clear that the two spaces are orthogonal. Signal Subspace data received by the array covariance matrix and eigenvectors corresponding to the signal component, the noise subspace from the covariance matrix of all the smallest eigenvalue (noise variance) eigenvector components.)

基于最小均方算法的自适应数字波束形成器程序(Algorithm based on minimum mean square adaptive digital beamformer program)