Box-muller-Data

说明：  这是一本matlab神经网络工具箱使用指南(This is a matlab Neural Network Toolbox User)

对心电信号的经典处理，多种滤波器的设置，包含比较全面的源码和解释，并在matlab中仿真(Classic ECG processing, various filter settings, including source code and more comprehensive explanation and simulation in matlab)

神经网络进行语音识别：/enframe.m，该函数将输入向量分为固定长度固定重叠量的帧。/SampleCreate.m,将取所有音频的mfcc系数处理成神经网络函数所需的输入格式(Neural networks for speech recognition)

自己编写的通用2维框架结构，可以计算模态、静力、动力响应 地震反应(I have written the common two-dimensional frame structure, you can calculate the modal, static and dynamic response of the seismic response)

三状态锁相环的matlab仿真程序，使用stateflow方法编译(Three state phase locked loop of matlab simulation program, use compiled stateflow method )

利用GUI功能完成包括AM，DSB，SSB，FM模拟调制在内的调制解调过程，参数可调。(GUI for analog modulation & demodulation, including AM, DSB, SSB, FM.)

最大团问题，matlab程序，无程序说明 (Maximum clique problem)

基于机器学习->增强型学习的路径规划算法实现，包括Q学习和动态学习。(Implementation of Reinforced Learning Algrithm for grid path planning problem, including Q-learning and Dynamic Learning.)

胡广书数字信号处理的MATLAB程序，函数按章节号命名(HU Guang-book digital signal processing of the MATLAB program)

包括：用基本粒子群算法求解无约束优化问题，用带压缩因子的粒子群算法求解无约束优化问题，用线性递减权重粒子群优化算法求解无约束优化问题，用自适应权重粒子群优化算法求解无约束优化问题，用随机权重粒子群优化算法求解无约束优化问题，用学习因子同步变化的粒子群优化算法求解无约束优化问题，用学习因子异步变化的粒子群优化算法求解无约束优化问题，用二阶粒子群优化算法求解无约束优化问题，用二阶振荡粒子群优化算法求解无约束优化问题(Include: using the particle swarm algorithm for unconstrained optimization problems, with compression factor of particle swarm algorithm for solving unconstrained optimization problem with linear decreasing weight particle swarm optimization for unconstrained optimization problems, an adaptive weight particle swarm optimization unconstrained optimization problems, random weight particle swarm optimization algorithm for unconstrained optimization problems, with the learning factor synchronous change of particle swarm optimization algorithm for unconstrained optimization problems, with the learning factor asynchronous changes in particle swarm optimization algorithm for solving unconstrained optimization problem , with the second particle swarm optimization for unconstrained optimization problems, with the second-order oscillating particle swarm optimization algorithm for unconstrained optimization problem)