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Matlab的数值拟合和插值方法介绍，内有程序说明和算法介绍。主要对最小二乘，线性回归作了介绍(Matlab Numerical fitting and interpolation methods introduce, within the description of the procedures and algorithms have introduction. Mainly on the least-squares, linear regression was introduced by)

说明：  Language 求已知数据点的拉格朗日插值多项式 Atken 求已知数据点的艾特肯插值多项式 Newton 求已知数据点的均差形式的牛顿插值多项式 Newtonforward 求已知数据点的前向牛顿差分插值多项式 Newtonback 求已知数据点的后向牛顿差分插值多项式 Gauss 求已知数据点的高斯插值多项式 Hermite 求已知数据点的埃尔米特插值多项式 SubHermite 求已知数据点的分段三次埃尔米特插值多项式及其插值点处的值 SecSample 求已知数据点的二次样条插值多项式及其插值点处的值 ThrSample1 求已知数据点的第一类三次样条插值多项式及其插值点处的值 ThrSample2 求已知数据点的第二类三次样条插值多项式及其插值点处的值 ThrSample3 求已知数据点的第三类三次样条插值多项式及其插值点处的值 BSample 求已知数据点的第一类B样条的插值 DCS 用倒差商算法求已知数据点的有理分式形式的插值分式 Neville 用Neville算法求已知数据点的有理分式形式的插值分式 FCZ 用倒差商算法求已知数据点的有理分式形式的插值分式 DL 用双线性插值求已知点的插值 DTL 用二元三点拉格朗日插值求已知点的插值 DH 用分片双三次埃尔米特插值求插值点的z坐标 (chazhi)

说明：  MATLAB 仿真MLSE，DFE，FFE均衡效率比较。(MATLAB simulation of MLSE, DFE, FFE balance efficiency comparisons.)

用matlab编写的关于图像的行分割和列分割算法，很实用(Prepared using matlab line on the image segmentation algorithm segmentation and out, very useful)

code for vision stuff homework related

相关的 BSS 盲源分离问题和 CS压缩感知的结合4篇论文打包，以及一个声音信号混合分离的简单实现(the realization of BSS(blind source separation) and CS(compressed sensing), and a sample of volume signal s matlab illustration)

智能优化算法标准测试函数，cec09动态问题测试函数(Benchmark Generator for CEC 2009 Competition on Dynamic Optimization)

说明：  运行混沌电路中的经典方程组——洛伦兹方程组，通过计算相图和李雅普诺夫指数图，分析其动力学行为。(Lorentz equations, a classical system of equations in chaotic circuit, are used to analyze its dynamic behavior by calculating the phase diagram and Lyapunov exponent diagram.)

无线传感器网的leach协议的实现。基于matlab。。(Wireless sensor networks leach protocol implementation. Based on matlab. .)

高阶谱分析工具箱，强烈推荐，共计58个函数，实现了高阶谱估计的几乎全部功能。本人在这里上传的文件，仅仅为了学术交流。希望大家都有机会掌握高阶谱估计。互相切磋，共同进步！(higher order spectral analysis toolkit, strongly recommend, for a total of 58 functions, to achieve the high-end of the spectrum is estimated that almost all functions. Here, I would upload documents, only to academic exchanges. Hope we have the opportunity to acquire higher-order spectrum estimation. Peers common progress!)