BP-wind-prediction

三种基本调制方式（2ask 2fsk 2psk）的仿真源码 解调方式为相干解调，过程较详细，推荐下载(Three basic modulation (2ask 2fsk 2psk) Demodulation of the simulation source code for the coherent demodulation, the process in more detail, it is recommended to download)

it is about ldpc codes

说明：  基于小波变换的LMS 可自动选择数据类型和噪声类型(LMS based on wavelet transform)

粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO， 是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。(Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years (Evolutionary Algorithm- EA). Kind, and simulated annealing algorithm PSO algorithm is similar evolutionary algorithms, it is also starting a random solution, through an iterative search for the optimal solution, which is also used to uate the quality through fitness solution, but it is simpler than genetic algorithm rules It has no genetic algorithm " crossover" (Crossover) and " variant" (Mutation) operation, which by following the current search to find the optimal value to the global optimum. This algorithm is its easy implementation, high accuracy, fast convergence, etc. attracted academic attention and show its superiority in solving practical problems. PSO algorithm is a parallel algorithm.)

用于图像的主成分变换，完成数据压缩的目的和数据信息的提取(transformation of features)

field oriented control for induction motor

in this package are the programs needed to solve any problems boundary value differential.

说明：  最小均方自适应滤波算法（LMS）与归一化最小均方自适应滤波算法（NLMS）的对比(Comparison of Least Mean Square Adaptive Filtering Algorithm (LMS) and Normalized Least Mean Square Adaptive Filtering Algorithm (NLMS))

介绍了用MATLAB模糊逻辑工具箱设计模糊控制器，并用SIMULINK进行仿真的一般方法(Introduced the fuzzy logic toolbox with MATLAB fuzzy controller design and simulation using SIMULINK general approach)

贝叶斯压缩感知 用于稀疏信号重建，基于贝叶斯理论(Adaptive compressive sensing, Bayesian model selection, compressive sensing (CS), experimental design, relevance vector machine (RVM), sparse Bayesian learning.)