jiefangcheng

EP1C6Q240C8的examples 鼠标口测试程序(The examples I EP1C6Q240C8 mouse test procedures)

Windowing, FIR filters

Simple and effective means of clustering any data for which a similarity matrix can be constructed. Does not require similarity matrix meet the standards for a metric. The algorithm applies in cases where the similarity matrix is not symmetric (the distance from point i to j can be different from j to i). And it does not require triangular equalities (e.g. the hypoteneus can be less than the sum of the other sides)

数字预失真Wiener模型的matlab实现(Digital predistortion Wiener model matlab implementation)

Implementation of Poly alphabetic Cipher

MTD primitives for XIP support. Architecture specific functions.

压缩感知基本理论：回顾与展望A201003-1461(Advances and Perspectives on Compressed Sensing Theory )

说明：  MATLAB 代码 第1章 BP神经网络的数据分类——语音特征信号分类 第2章 BP神经网络的非线性系统建模——非线性函数拟合 第3章 遗传算法优化BP神经网络——非线性函数拟合 第4章 神经网络遗传算法函数极值寻优——非线性函数极值寻优 第5章 基于BP_Adaboost的强分类器设计——公司财务预警建模 第6章 PID神经元网络解耦控制算法——多变量系统控制 第7章 RBF网络的回归--非线性函数回归的实现 ....等58章(MATLAB code The first chapter is BP neural network data classification -- speech characteristic signal classification The second chapter is the nonlinear system modeling of BP neural network nonlinear function fitting The third chapter, genetic algorithm optimization BP neural network - nonlinear function fitting The fourth chapter, neural network, genetic algorithm, function extreme value optimization nonlinear function extremum seeking The fifth chapter is based on BP_Adaboost's strong classifier design -- the company financial early-warning model The sixth chapter is PID neural network decoupling control algorithm multivariable system control The seventh chapter is the regression of RBF network the realization of nonlinear function regression .........the last is 58 chapters)

用于做统计分析的matlab 程序包,各种基本统计分析的函数都有，很好用。(For matlab to do statistical analysis package, a variety of basic statistical analysis functions are well used.)

一种简单快速的视频分割方法，针对多媒体视频序列(A simple method of fast video segmentation, video sequences for multimedia)