fuzzy-PID-contro

经验小波变换结合EMD的自适应性和小波分析的理论框架,Gilles提出了一种称为经验小波变换(EWT)的自适应信号处理方法.其核心思想是通过对信号的Fourier谱进行自适应划分,建立合适的小波滤波器组来提取信号不同的AM-FM成分.(Empirical wavelet transform)

搜集了一些关于matlab中系统能控性和能观设计的详细介绍的一些资料，应该有人需要(Matlab collected some information on the system controllability and observability of the design details of some of the information, should someone need to)

mmse algorithm in ofdm matlab code

matlab编写克里金差值的说明技术文档，包含具体的算法(The kriging software described in this document was developed by Dezhang Chu with funding the National Science Foundation through the U.S. GLOBEC Georges Bank Project s Program Service and Data Management Office. It was originally inspired by a MATLAB toolbox developed by Yves Gratton and Caroline Lafleur (INRS-Océanologie, Rimouski, Qc, Canada), and Jeff Runge (Institut Maurice-Lamontagne, now with University of New Hampshire). This software may be reproduced for noncommercial purposes only.)

Model on Matlab of acoustic position system

说明：  matlab电路仿真,直流暂态电路的防真. 有源程序,也有simulink模型(Matlab circuit simulation, transient DC Circuit-true. A source also Simulink model)

通过构造加博函数进行加博滤波实现对指纹图像的分割(By constructing Gabor function Gabor filter is on the fingerprint image segmentation)

采样时间：1E-6秒 脉冲长度：200E-6秒（脉冲宽度=200个样本） 脉冲间隔：1E-3秒（脉冲周期=1000个样本） 初始频率啁啾：DC至200 kHz（目标频率） 扫描时间：200E-6（200个样本） (Sample Time: 1e-6 sec Pulse Length: 200e-6 sec (Pulse width=200 samples) Pulse Interval: 1e-3 sec (Pulse period=1000 samples) Chirp: DC (initial freq) to 200 kHz (target freq) Sweep time: 200e-6 (200 samples))

几个关于有限元分析的代码，《结构分析的有限元法与matlab编程》-徐荣桥(Several finite element analysis on the code, " Structural Analysis of the finite element method and matlab programming" - Xu Rong Bridge)

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)