tuoyuan2

The package contains matlab coding and algorithms which will be easy to understand and provides a variety of strategies to develop a good programming skill

DWT COde using folding coefficient.............

一种结合PSO及改进BP网络的辨识方法 很好的微粒群应用算法辨识效果很好(A combination of PSO and the improved BP network identification method of application of particle swarm algorithm is a very good very good identification results)

image fusion using particle of swarm optimastion

关于端点检测的几种方法，语音样本是自己录制的，对传统算法做了一些改进，加入了去噪，去噪之后再进行端点检测，均调通 vad0303：自己设置调整门限为一定值 vad0310：根据能量值和过零率设置门限，自适应门限值 vad0310_2：基于比例因子的门限自调整 vad0310.m加入了噪声，端点检测前都噪声进行了处理 entropy.m：基于自适应子带频谱熵的稳健性语音端点检测 可用于语音增强及端点检测 dbdoor.m：双门限算法，用于语音端点检测。可以通过调整门限值，并加入门限自适应算法，实现语音端点检测(Several methods on endpoint detection, recording their own voice samples, the traditional algorithm has made some improvements, adding a de-noising, and then after de-noising endpoint detection are transferred through)

matlab四阶龙格库塔法，，，，，，，，，，，，，，，，，，(runger kutta)

expand axes for matlab

MATLAB函数参考手册，查看matlab函数作用以及功能。( SVMLSPex02.m Two Dimension SVM Problem, Two Class and Separable Situation Difference with SVMLSPex01.m: Take the Largrange Function (16)as object function insteads ||W||, so it need more time than SVMLSex01.m Method from Christopher J. C. Burges: "A Tutorial on Support Vector Machines for Pattern Recognition", page 9 Objective: min "f(A)=-sum(ai)+sum[sum(ai*yi*xi*aj*yj*xj)]/2" ,function (16) Subject to: sum{ai*yi}=0 ,function (15) and ai>=0 for any i, the particular set of constraints C2 (page 9, line14). The optimizing variables is "Lagrange Multipliers": A=[a1,a2,...,am],m is the number of total samples.)

matlab编的水平集分割的一些好东东, 适用于模糊图像的目标提取，希望能共勉(some program of matlab for image segmentation and small target extraction)

finit difference waveguide