Face-Capture

particle swarm optimization codes

Online identify the plant dynamic by using intelligent architecture, here using RBF Neural network for the plant.

Introduction of the Particle Swarm Simulated Annealing Algorithm in Function Optimization

RBF方法对一维函数进行插值实例，选用的函数为MQ函数，可与高阶多项式插值对比，说明RBF方法克服了龙格振荡问题。(RBF method for one dimentional function interpolation, where the Runge oscillation is disappear.)

k means techniques de classification non supervisée (clustering) les plus utilisées. Etant donné un entier K, K-means partitionne les données en K groupes, ou "clusters", ou "classes" ne se chevauchant pas. Ce résultat est obtenu en positionnant K "prototypes", ou "centroï des" dans les régions de l espace les plus peuplées. Chaque observation est alors affectée au prototype le plus proche (règle dite "de la Distance Minimale"). Chaque classe contient donc les observations qui sont plus proches d un certain prototype que de tout autre prototype

This algorithm is ADI algorithm.

matlab程序运行时导入数据文件作为输入参数，验证可用，用于时频分析算法，包括调制，解调，信噪比计算。( Import data files as input parameters matlab program is running, Verification is available, For time-frequency analysis algorithm, Includes the modulation, demodulation, signal to noise ratio calculation.)

voie recording codes

A new blind adaptive multiuser detection scheme based on a hybrid of Kalman filter and subspace estimation is proposed. It is shown that the detector can be expressed as an anchored signal in the signal subspace and the coefficients can be estimated by the Kalman filter using only the signature waveform and the timing of the desired user.(A new blind adaptive multiuser detection s cheme based on a hybrid of the Kalman filter and subs pace estimation is proposed. It is shown that th e detector can be expressed as an anchored signa l in the signal subspace and the coefficients ca n be estimated by the Kalman filter using only th e signature waveform and the timing of the desir ed user.)

说明：  一阶倒立摆仿真matlab程序，包含仿真结果和simulink仿真(Matlab program of one order inverted pendulum simulation)