Automaticdistinguishing

This is a program for Binary Genetic Algorithm

运用MMSE方法的波束形成，对空间信号起滤波作用(MMSE method for beamforming)

说明：  混沌时间序列分析及其应用混沌时间序列分析及其应用

Matlab Hankel变换源代码，可以直接当做MATLAB toolbox来使用( MATLAB toolbox ________________________________________________________ Hankel transform ________________________________________________________ ** Contents 1. Introduction 2. Requirements 3. Implementation details 4. References 5. Copyright 6. Warranty 7. History 8. Download 9. Trademarks ** Publisher Marcel Leutenegger marcel.leutenegger@epfl.ch EPFL STI IOA LOB BM 4.143 Tel: +41 21 693 77 19 Station 17 CH-1015 Lausanne 1. Introduction The Hankel transform of order n transforms rotationally symetric inputs in a computationally efficient manner. In particular, the Hankel transform of order 0 is equivalent to the two-dimensional Fourier transform of a rotationally symetric input. This package contains four implementations of the Hankel transform and the inverse Hankel transform, respectively. 2. Requirements ?MATLAB 6.0 or newer. 3. Implementation details The package ships fou)

matlab在大气科学中的应用~这是介绍如何在大气科学研究中使用matlab的入门教程(matlab in atmospheric science applications- this is how to use matlab in atmospheric sciences Tutorial)

Another advantage is that geometric properties of the curve are easily determined from a particular level set of the surface . For example, the normal vector for any point on the curve C is given by:

kalman滤波及坐标转换 包括笛卡尔坐标与极坐标，gauss噪声，地理坐标和ECEF坐标转换函数(kalman filter)

LibSVM代码说明，有助于对算法实现的理解。(LibSVM Guide)

小波分解和重构小波分解和重构小波分解和重构小波分解和重构(thr=sigma*(2*lgN)1/2/lg(j+1) 用[x,xn]=wnoise(2,10,6) 产生噪声测试数据-The following is Part I of a of hard and soft threshold denoising matlab procedure is the following hardware and software, I made a threshold denoising matlab program: thr = sigma* (2* lgN) 1/2/lg (j+1) by [x, xn] = wnoise (2,10,6) noise test data)

Finding the Nearest Orthonormal Matrix In some appoaches to photogrammetric problems (perhaps inspired by projective geometry), an estimate M of an orthonormal matrix R representing rotation is recovered. It is then desired to find the “nearest’’ orthonormal matrix. While this two step approach — first finding a “best fit’’ matrix without enforcing orthonormality,and then finding the nearest orthonormal matrix — is not to be recommended, it may be of interest to find a solution to this problem nevertheless.