一个流形学习算法集合程序

粒子群优化算法优化RBF神经网络程序，可用在模式分类等方面(Particle swarm optimization algorithm optimization RBF neural network program can be used in pattern classification, etc.)

Quasi-Orthogonal Space-Time-Frequency Trellis Codes for MIMO-OFDM Systems

2代小波示意程序，此程序用提升法实现第二代小波变换 -two generation wavelet indicate procedures, the procedures used to enhance law to achieve the second generation wavelet transform

LabVIEW的脚本节点允许用户执行外部脚本。具体地讲 ,使用脚本节点可以执行 MATLAB 脚本。由于许多人都曾经开发和使用过 MATLAB 脚本称为 m 文件,本论文将集中讨论使用 MATLAB 脚本节点来执行MATLAB脚本文件,其具体实现过程如下: (Control systems designed by humans are used to extend their physical capabilities,to compensate for their physical limitations,to relieve them of routine or tedious tasks,or to save money.)

本程序基于滑动窗口可以实现对一维曲线平滑及降噪，根据有用信号的频率，选取合适的窗口宽度。(This procedure can be achieved based on the sliding window, select the appropriate window width of one-dimensional curve smoothing and noise reduction, according to the frequency of the desired signal.)

multi - objective optimisation

说明：  遗传算法路径规划MATLAB仿真，基于栅格图环境建模，以遗传算法优化路径。(Genetic Algorithms for Optimal Path Planning)

环境下构建一种新的系统辨识仿真工具箱(SIST: System Identification Toolbox)的原理与实现,讨论了在MATLAB 环境下工具箱的数据和算法结构形式,以及利用GUIDE完成图行界面的设计,用MATLAB 与C++混编技术实现物理系统的I/O 接口和系统辨识... (err)

该代码用于实现粒子滤波视觉目标跟踪(PF)、卡尔曼粒子滤波视觉目标跟踪(KPF)、无迹粒子滤波视觉目标跟踪(UPF)。它们是本人这两年来编写的核心代码，用于实现鲁棒的视觉目标跟踪，其鲁棒性远远超越MeanShift(均值转移)和Camshift之类。用于实现视觉目标跟踪的KPF和UPF都是本人花费精力完成，大家在网上是找不到相关代码的。这些代码虽然只做了部分代码优化，但其优化版本已经成功应用于我们研究组研发的主动视觉目标跟踪打击平台中。现在把它们奉献给大家！(These codes are used to realize particle filter based visual object tracking (PF), kalman particle filter based visual object tracking, unscented particle filter based visual object tracking. Their robustness is far beyond the classical visual object tracking algorithms such as Mean-Shift (MeanShift) and CamShift。The codes of KPF and UPF for visual object tracking cost a great of my energy, and you can not find any relating algorithm codes on internet! Our research group have optimized these codes and applied them to develop a platform for active visual object tracking. Now, I dedicate them to you and wish you love them! )

自适应的LMS算法和RLS算法的实现 以及其比较(LMS adaptive algorithm and the realization of the RLS algorithm and its comparison)