Meteorological-Data-Processing

定义了通信中帧格式，用matlab代码实现了这个过程，可以自定义巴克码的长度，接收端可以采用滑动相关法捕获该帧(The definition of a communication frame format, using matlab code to achieve this process, can customize the length of Barker Code, the receiving end of sliding correlation method can be used to capture the frame)

信号处理 music,求根算法源程序及仿真很经典。(Signal processing music, Roots element program and the simulation algorithm)

粒子群优化支持向量机的算法，主要是用于优化两个参数(PSO LSSVM algorithm)

基于matlab程序对矩阵转置编写的程序，对于矩阵转置很有帮助(Matlab program based on programs written in matrix transposition, matrix transpose for helpful)

Hand Gesture Recognition NOTES: 1) For the details of the algorithm investigate the following images: -AlgorithmOverall.jpg -MKRoDAlgorithm.jpg 2) The prototype is implemented on MATLAB 7.0 and revised in MATLAB 7.10.0 3) The backgrounds of input images have to be purely ‘black’ and the details of the content(palms, fingers) must be clear for accurate recognition of the ASL. 4) A reduced ASL dataset is used. The dataset contains the following ASL gestures: "b,c,h,i,o,l,y". ---------------------------------------------------------------- Use execHGR.m inside the Project folder in order to execute the program. I hope you will enjoy it.

Kolda Tensor Factorization toolbox. Useful for tensor signal processing

维特比译码算法，采用matlab语言进行编写，与自带的一致，可验证(Viterbi decoding algorithm, using matlab language writing, consistent with the built-in, verifiable)

综合自然激励技术和特征系统实现算法，进行了模拟环境激励下结构的时域模态参数识别(In the method, the transition from structural random response to deterministic response was realized by the natural excitation technique(NExT))

说明：  高通滤波的matlab程序的实现代码matlab程序(High-pass filter matlab program implementation code)

support vector classification machine ％ soft margin ％ uses "kernel.m" ％ ％ xtrain: (Ltrain,N) with Ltrain: number of points N: dimension ％ ytrain: (Ltrain,1) containing class labels (-1 or +1) ％ xrun: (Lrun,N) with Lrun: number of points N: dimension ％ atrain: alpha coefficients (from svcm_train on xtrain and ytrain) ％ btrain: offest coefficient (from svcm_train on xtrain and ytrain) ％ ％ ypred: predicted y (Lrun,1) containing class labels (-1 or +1) ％ margin: (signed) separation from the separating hyperplane (Lrun,1(support vector machine classification% s oft margin% uses "kernel.m"%% xtrain : (Ltrain, N) with Ltrain : number of points N : % ytrain dimension : (Ltrain. 1) containing class labels (-1 or 1)% xrun : (Lrun, N) with Lrun : number of points N : % atrain dimension : alpha coefficients (from svcm_train on xtrain and ytrain)% btrain : offest coefficient (from svcm_train on xtrain and ytrain)%% ypred : predicted y (Lrun. 1) containing class labels (-1 or 1)% margin : (signed) separation from the separating hyper plane (Lrun, 1)