dimats

说明：  在三维空间中画泡泡,可以指定在三维空间中的x,y,z的坐标以及泡泡的半径r和颜色c(RGB).(BUBBLEPLOT3(x,y,z,r), where x, y, z and r are four vectors of the same length, plots bubbles of radii r in 3-space with centers at the points whose coordinates are the elements of x, y and z. If r is a matrix of size numel(x)x3, BUBBLEPLOT3 produces ellipsoids with centers x(i),y(i),z(i) and radii r(i,1), r(i,2) and r(i,3). BUBBLEPLOT3(x,y,z,r,c), where c is a rgb-triplet array (in [0,1]) with numel(x) rows, plots bubbles with colours specified by c. )

自己做的采用60度坐标系的三电平SVPWM模块 用的是matlab2009b (60-degree three-level SVPWM module Matlab2009b)

This code shows in a simple way the implementation of 2 dimention finite difference time domain simulation. We also implement perfectly match layer at the border.

MPSK Modulation Code & BER SNR Calculation

通过对语音信号的采集和AD50数模转换实现语音信号的处理，并通过C54试验台可以很好的实现语音再现。FIR数据滤波数据需要通过MATLAB来实现。(Through the acquisition and AD50 voice signal digital-analog conversion of voice signal processing, and through the C54 test bed can be a very good voice reproduction. FIR data filtering data to achieve through MATLAB.)

该matlab代码实现了“综合多分支分裂式层次化聚类” (Matlab implementation of Omnibus Multi-Branching Divisive Hierarchical Clustering (OMBDHC) “A competitive omnibus performance criterion for divisive multi-branching hierarchical clustering” by Soeria-Atmadja et al. (submitted). Note that OMB-DHC package is implemented in Matlab code and therefore demands the Matlab core program, as well as the Statistics toolbox of Matlab. Divisive hierarchical clustering (DHC) has emerged as a promising alternative for the identification of sub-structures in multivariate data. Of particular interest is multi-branching DHC, which allows flexible numbers of subclusters at each hierarchical level. One poorly explored issue in multi-branching DHC concerns the actual importance of the two performance criteria (and their associated algorithms) to automatically create clusters and select number of clusters, respectively. Another interesting but hitherto unexplored issue is the possibility to employ a single omnibus performance criterion that guide)

《Matlab神经网络30个案例分析》程序和数据 (" Matlab neural network analysis of 30 cases," the program and data)

数据挖掘中k均值划分聚类算法。输入对象的数据集矩阵和簇的数量，使用欧拉距离计算对象之间的相拟度(K-means partitioning clustering algorithm in data mining. Input object data sets matrix and the number of clusters, using euler distance calculation。)

时频原子分解算法利用冗余特性分解成多个时频原子库来进行信号特征的处理分析(Time-frequency atom decomposition algorithm using redundant features broken down into processing and analysis the multiple frequency atoms library to signal characteristics)

将视觉注意力用于同步定位于构图的一篇经典文献，详述了视觉注意力理论及其用于SLAM的具体步骤(A classic literature, visual attention for simultaneous localization composition detailed theory of visual attention and its concrete steps for SLAM)