Mdocument_matlab

pb通用过滤排序,解压后可在pb中查看源码(powerbuilder sort or filter)

基于修改模型的冲突证据组合方法,林志贵,上 海 交 通 大 学学报(Based on the modified model of the conflict in the evidence combination method,林志贵, Journal of Shanghai Jiaotong University)

linux下matlab可用的最小二乘法支持向量机ls-svm，c语音代码。(matlab under linux available method of least squares support vector machine ls-svm, c voice code.)

matlab求卷积和卷积积分等，就是卷积的应用的，看吧吧吧吧。(matlab seeking, such as convolution and the convolution integral is the convolution of the application, and see it right now.)

对于抽样定理的验证，十分好，二十字不太好的(For the sampling theorem verification, very good, not good twenty words)

QPSK的误符号率以及QPSK的旋转星座的误符号率源代码。(Rotation QPSK symbol error rate as well as QPSK constellation symbol error rate of the source code.)

function to easily save cell matrix with mixed data. Example file is included

利用EM算法对状态空间模型中的参数进行辨识，效果良好(The EM algorithm is used to identify the parameters in the state space model, and the result is good.)

Generate 100 samples of a zero-mean white noise sequence with variance , by using a uniform random number generator. a Compute the autocorrelation of for . b Compute the periodogram estimate and plot it. c Generate 10 different realizations of , and compute the corresponding sample autocorrelation sequences , and . Compute the average autocorrelation sequence as and the corresponding periodogram for . d Compute and plot the average periodogram using the Bartlett method. e Comment on the results in parts (a) through (d). (Generate 100 samples of a zero-mean white noise sequence with variance, by using a uniform random number generator.a Compute the autocorrelation of for. B Compute the periodogram estimate and plot it. C Generate 10 different realizations of, and compute the corresponding sample autocorrelation sequences, and. Compute the average autocorrelation sequence as and the corresponding periodogram for. d Compute and plot the average periodogram using the Bartlett method. e Comment on the results in parts (a) through (d).)

Demo of some Garch models, include ugarch, dcc-garch, ica-garch, and neural network garch, and ica-nn-garch. the last two model are proposaed by me