mariner

使用MATLAB_Engine与C混合编程(MATLAB_Engine andC hybrid programming)

用于车牌识别，个人感觉比较好，大家可以看一下(For license plate recognition, personal feeling better, we can look at)

Neighborhood rough set based heterogeneous feature subset selection

采用KPCA方法的人脸识别算法，包含算法的matlab实现源码及相关测试、训练数据集(KPCA based face recognition algorithm, matlab source code of the algorithm implementation and related testing, training data set contained)

基于matlab利用一维FDTD方法对电磁波传播及反射透射进行仿真(Based on matlab using one-dimensional FDTD method and the reflection and transmission of electromagnetic wave propagation simulation)

二用户CDMA系统，信道为加性高斯信道，使用BPSK调制，15位M序列扩频，可以正确解扩解调。 输出为2用户的基带信号、扩频信号、PSK调制信号、解调信号的时域和频域特性，给出两个用户分别的误码率。 (Second, the user CDMA system, channel for the additive Gaussian channel, using BPSK modulation, 15 M Sequence Spread Spectrum, you can correct demodulation despreading. Output of 2 user' s baseband signal, spread spectrum signal, PSK signal modulation, demodulation signal time domain and frequency domain characteristics of the two users are given the bit error rate, respectively.)

PSOt - a Particle Swarm Optimization Toolbox for use with Matlab. A Particle Swarm Optimization Toolbox (PSOt) for use with the Matlab scientific programming environment has been developed. PSO is introduced briefly and then the use of the toolbox is explained with some examples. A link to downloadable code is provided.

对一个给定的状态转移矩阵求其联合分布矩阵，联合熵，平均互信息量以及共熵。可以画出平均互信息量的曲线(For a given state transition matrix of their joint distribution matrix, the joint entropy, mutual information and the average total entropy. Can draw the curve of the average mutual information)

fuzzy model reference learning control

说明：  通信信号的调制信息包含在信号的瞬时幅度、相位、频率的变化之中，不同的信号其频谱也呈现不同的特征，通过提取瞬时幅度、相位、频率以及频谱的参数统计特征，可以识别不同的通信信号。通常是利用对瞬时幅度、瞬时相位，瞬时频率和信号功率谱进行某种变换而得到可以明显区分各种信号的特征参数。(Communication signal modulation information is contained in the signal instantaneous amplitude, phase, frequency changes, the spectrum of different signals also show different characteristics, by extracting the instantaneous amplitude, phase, frequency and statistical characteristics of the parameters of the spectrum, you can identify different communication signals. Usually by the use of instantaneous amplitude, instantaneous phase, instantaneous frequency and signal power spectrum a transformation which can be clearly distinguished by the characteristic parameters of various signals.)