Continuous-morlet-wavelet-transform

说明：  ：Mean—shift算法是一种非参数密度估计算法，可以实现快速的最优匹配，在目标的实时跟踪领域起着非常 重要的作用。为了有效的将Mean—shift算法应用到灰度图像中，采用了以方向直方图建立目标模型的策略，提出了在灰 度图像中以Mean—shift为核心的目标跟踪算法。实验结果表明，该算法具有不受光照条件影响的优点，在低对比度的情 况下仍能实现稳定、实时的跟踪目标。(: Mean-shift algorithm is a nonparametric density estimation algorithm, the optimal matching can be fast, real-time tracking fields in the target plays an important role. In order to effectively Mean-shift algorithm will be applied to the gray image, the histogram used to establish the direction of the strategy target model is proposed in the gray image to Mean-shift tracking algorithm as the core. Experimental results show that the algorithm has the advantage of not lighting conditions, in the case of low contrast can still achieve stability, real-time tracking of targets.)

用matlab编写的AR谱分析程序及源数据(AR spectrum)

achartengine 动态折线图的实现(Realization of dynamic line graph achartengine)

A filter is a system which modifies some special frequencies reletive to the others. As a result it is applicable in some applications when it is necessary to have different gains & phase shifts at different frequencies to perform specific filtering tasks. For example in an audio file which is corrupted by noise it is convinient to use a filter to cancel those frequencies which are affected by noise and consequently having a better sound quality. During this MATLAB experiment we are trying to cancel the noise frequencies out of the original signal frequencies to get the original signal. Due to do this task, different types of filters such as FIR and IIR filters are used. In FIR filters, we use two type of common windows such as fixed window like Hanning and adjustable window like Kaiser. In IIR filters four different types of filter such as Butterworth, Chebyshev I, Chebyshev II, Elliptic are used.

Split & Merge Algorithm

dIVISIVE CLUSTER ALGORITHM

说明：  对数值进行分析，AP聚类算法是基于数据点间的"信息传递"的一种聚类算法。与k-均值算法或k中心点算法不同，AP算法不需要在运行算法之前确定聚类的个数。AP算法寻找的"examplars"即聚类中心点是数据集合中实际存在的点，作为每类的代表(For numerical analysis, AP clustering algorithm is based on the "information transfer" between data points. Unlike k-means algorithm or k-center algorithm, AP algorithm does not need to determine the number of clusters before running the algorithm. The "examples" searched by AP algorithm is the actual points in the data set as the representative of each class)

matlab 信号分析详解(matlab design)

说明：  张志涌版，根据matlab R2010a版来编排的Matlab教材。值得matlab学习者下载，很与时俱进的东东。(The handbook of matlab R2010a.)

用matlab自编的基于自适应局部线形化的软件可靠性模型.效果非常良好.源程序和数据集都有,可以直接运行.(using Matlab-based adaptive self Local Alignment of software reliability models. The effect was very good. source code and data sets have, and can directly operation.)