bp

sobel边缘检测在matlab环境下实现的源程序代码(Sobel edge detection in matlab source code realization)

Matlab程序写的产生各种正弦波形的程序，带有界面，并可以保持为wave文件。(Matlab program written procedures produce all kinds of sine wave-shaped, with the interface, and can be maintained for the wave file.)

Resource allocation in LTE matlab code

关于目标追踪的算法,用卡尔曼滤波方法，论文后面有相关的仿真图(a new way to track)

随着城市经济的快速发展和城市人口的不断增加，人类活动对城市环境质量的影响日显突出。(With the city' s rapid economic development and urban population increases, human activities on urban environmental quality more evident.)

通过主成分分析和偏最小二乘分析，然后画出数据的PCA主轴和PLS主轴(Principal component analysis and partial least squares analysis, and then draw the PCA and PLS spindle axis data)

进行核主成分分析，KICA，克服主成分分析不能提取非线性特征，提取核主成分(Nuclear principal component analysis, KICA, extraction of principal components)

各种不同信号调制方式的matlab源程序(Various signal modulation matlab source)

este documento se basa en la simulación y programación de la respuesta de un tiro parabólico en el cual podremos configurar tanto la altura en el el eje y como la distancia en el eje x

逐步判别分析的主函数 用于分类 [sel,c,c0,re,P]=StepclaassV2(data,[50 50 50],data,10) 输入变量 x为训练集.每行为一个样本，每列为一个变量. Class_x,为训练集的分类情况，一行，为各类样本数量,例如[5 6 9] Test为待分类样本. 输出变量：sel为选择的变量序号，c,c0为拟合出的判别函数.re为对Test的判别结果,P为其后验概率. author 王新 2012.4.8 例子Sample: load fisheriris x=meas Class_x=[50,50,50] Test=meas(1:5,:) Fa1=4 [sel,c,c0,re,P]=StepclaassV2(x,Class_x,Test,Fa1)( Stepwise discriminant analysis for the classification of the main function [sel, c, c0, re, P] = StepclaassV2 (data, [50 50 50], data, 10) input variables x as the training set, each conduct a sample of each as a variable. Class_x, the classification for the training set, a row, the number of samples for all types, for example, [5 6 9] Test sample to be classified. output variable: sel for the selected variables serial number, c, c0 is fitted discriminant function. re discrimination results for the Test, P its posterior probability. author Wang 2012.4.8 examples Sample: load fisheriris x = meas Class_x = [50,50,50] Test = meas (1:5, :) Fa1 = 4 [sel, c, c0, re, P] = StepclaassV2 (x, Class_x, Test, Fa1))