relayPuplinkPV2

采用ssda基本算法在一幅图像中找到与模板图像相匹配的坐标位置(Used ssda method to found a coordinate position that the template image matched in a large image )

Bluetooth Voice Transmission Matlab/Simulink R13 Version

一个MATLAB程序，用以实现基于最小均方误差算法的自适应均衡器，通常可以直接应用在数字通信系统中(A MATLAB program used to implement an LMS adaptive equalizer which can be directly applied in the digital communication systems)

软件程序按照发射端所掌握的各用户信道状态信息的程度共分为两部分：即完整信道状态信息(CSIT)和部分信道状态信息(CSIP)。其中，每一部分都包括预编码(precoding)和用户调度(scheduling) 在CSIT中，precoding又按照各用户的数据流数分为单数据流和多数据流两种情况。在每种情况下，首先考察了不同预编码算法的性能表现，包括两种ZF、MMSE、SINR、SLNR。之后又考察了功率分配算法的性能表现（文件名中含有PD表明其含有功率分配的过程）。按照不同指标进行功率分配的，在文件名中进行了区分，如PD_CN代表以信道范数为参考指标进行功率分配。Scheduling部分首先观察了RoundRobin、MaxH和MMSLNR三种算法的性能对比。之后在Kc和Round部分分别观察了不同预选用户数和不同最大替换轮数下MMSLNR算法的表现。 在CSIP中，只对各用户单数据流的情况进行了仿真。采用的预编码算法主要有DSLNR（即直接运用CSIT下的预编码算法）、ESLNR（即对SLNR进行均值计算的，在CSIP中，引入均值计算的与SLNR有关的算法，其文件名中都有modified以示区别）、EMMSE（即陈明老师那边的那篇文章中的预编码算法）。Scheduling中也只是简单的观察了RoundRobin、MaxH、DMMSLNR和EMMSLNR（前者没有均值计算，后者有）的性能对比。(The degree of channel state information for each user software program in accordance with the master transmitter consists of two parts : the complete channel state information (CSIT) and partial channel state information (CSIP). Wherein , each of which comprises a pre- coding (precoding) and the user scheduling (scheduling) In CSIT in , precoding and each user according to the number of data streams into a single data stream and multiple data streams in both cases . In each case , first examine the performance of different pre- coding algorithm, including two ZF, MMSE, SINR, SLNR. After they inspected the power allocation algorithm performance ( file name contains PD showed that it contained power allocation process ) . According to different indicators for power distribution , make a distinction in the file name , such as PD_CN representative channel norm-referenced index for power distribution . Scheduling section first observed the performance comparison RoundRobin, MaxH and MMSL)

改进的神经网络PSO,主要用于成功度评价,本例是电厂的成功度评价模型和数据.(Improved neural network PSO, mainly used in the successful evaluation, which in this case is the success of the plant model and data evaluation.)

tp matlab bien explique et commentee

统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines( This section should give the reader a quick overview of the methods implemented in STPRtool. • Analysis of linear discriminant function: Perceptron algorithm and multiclass modification. Kozinec’s algorithm. Fisher Linear Discriminant. A collection of known algorithms solving the Generalized Anderson’s Task. • Feature extraction: Linear Discriminant Analysis. Principal Component Analysis (PCA). Kernel PCA. Greedy Kernel PCA. Generalized Discriminant Analysis. • Probability distribution estimation and clustering: Gaussian Mixture Models. Expectation-Maximization algorithm. Minimax probability estimation. K-means clustering. • Support Vector and other Kernel Machines: Sequential Minimal Optimizer (SMO). Matlab Optimization toolbox based algorithms. Interface to the SVMlight software. Decomposition approaches to train the Multi-class SVM classifiers. Multi-class BSVM formulation trained by Kozinec’s algorithm, Mitchell- Demyanov-Molozenov algorithm )

基于MP的时间频率分布程序，该程序可以有效的将信号的时频分布显示出来(MP-based time-frequency distribution of program that can effectively time-frequency distribution of the signal displayed)

filtering ecg signal

GPM1002B0 初始化代码，颜色艳丽，可以直接使用(GPM1002B0 initialization code)