SVM_lzb1p0

关于最大似然重建方法的实现，可用于tomography reconstruction(This is the code for maximum likelihood expectation maximum reconstruction method which is frequently applied in tomography reconstruction, such as CT and PET)

非线性动力学-分岔图-matlab-程序，弹簧质量系统在简谐激励作用下的的首破振动(Nonlinear dynamics- bifurcation diagram-Matlab-program, the spring mass system under harmonic excitation is broken vibration)

OQAM pre processing

MIMO成像,Dimensional boundary imaging use in free space or in shallow ground penetrating radar(Dimensional boundary imaging use in free space or in shallow ground penetrating radar)

全面系统地给出鲁棒设计的源程序及运算实例，希望对研究鲁棒的有所帮助(Comprehensively and systematically given robust design and operator of the source code examples, I hope the study will help Robust)

对lbfgsb优化算法的Matlab仿真( Matlab simulation of Optimization lbfgsb)

此为基于二代提升小波的阈值压缩算法源码，其中可以设置小波变换的分解层数，使用的小波名称，及各层阈值设置计算公式中的参数。并将低频系数转化为十六进制，方便在其上进一步压缩，如采用Huffman压缩等，程序思路清楚，附有完整的注释，可以使用多种小波，并且很好得体现了二代小波的思想，对于初学小波者帮助很大。(。-based on the second generation of this upgrade wavelet compression algorithm threshold source, which can set wavelet transform decomposition level, the use of wavelet name, threshold levels and set the formula for calculating the parameters. And low-frequency coefficients into hexadecimal facilitate its further compression, such as the Huffman compression. procedures ideas clearly, with the integrity of the Notes, you can use a variety of wavelet, and reflected very well in the second generation wavelet thinking, For beginners who wavelet of great help. )

自己写的关于语音分帧，加窗，去噪，端点检测方面的程序，可成功调试 (Write about the voice sub-frame, adding windows, noise reduction, endpoint detection of the procedures, can be successfully debug)

是电力系统的IEEE标准算例的OPENDSS编写好的额程序，里面包含有短路算法(Is the IEEE standard power system operator OPENDSS writing good example of the amount of the program, which contains the shortest path 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)