资源列表
FUZZCLUST2
- 这是接着上一次的一些大家很可能用到的聚类分析方法，有PCA等，希望能给大家一些帮助。-then this is the last time some people may use the cluster analysis method, PCA. I hope that it provides some help.
binomial
- ％ binomial.m by David Terr, Raytheon, 5-11-04, from mathworks.com ％ Given nonnegative integers n and m with m<=n, compute the ％ binomial coefficient n choose m.
FastICA_2[1].1
- FastICA的Matlab程序，欢迎大家指教！-FastICA the Matlab program, we are happy to improve!
AllNeuralNetworkCompute
- 包含6个*.m文件，分别是adline网络，bp网络，hopfiled网络，字符识别，学习速度自适应，和增强型lms算法的六个仿真算法程序，真是我的珍藏，这次全抖出来了。-contains 6 m *. documents were adline network bp network hopfiled network, character recognition, adaptive learning speed, lms and enhanced algorithm simulation alg
fastslam_web
- FastSLAM1.0/2.0的仿真，在matlab环境下实现。对研究移动机器人同时定位与建图的研究者是非常不错的参考。-FastSLAM1.0/2.0 the simulation environment in Matlab under. Mobile robots to research the same time positioning and building plans of researchers is a very good reference.
lorenzsystembyinline
- 利用Maltab求解变参数lorenz方程,在非线性动力学和混沌研究中经常遇到类似的问题。本程序也可以求解类似的有变参数的微分方程系统如Chen system, Lv system, Rossler system 等。-use Maltab variational parameters lorenz equation, Nonlinear Dynamics and Chaos often encountered similar problems. The procedures also can
adaptive_LMS
- 自己写的基于LMS的自适应噪声抵消,例子是对一WAV声频信号去噪,效果不错,对这方面感兴趣的可以-wrote based on the LMS adaptive noise cancellation, for example, is a WAV audio signal denoising. good results, with interested can s
geap
- 自己编写的全主元高斯消去法解线性方程组的matlab函数。特点：运行稳定，适合于工程计算；结构清楚，注释详尽，非常适合于初学者。-their preparation of all PCA Gaussian elimination method for solving linear equations of Matlab function. Features : stable operation, which is suitable for engineering calculations; St
classification_error
- Find a classification error for a given decision surface D and a given set of patterns and targets -Find a classification error for a given dec ision surface D and a given set of patterns and ta rgets
MinimumCost
- Classify using the minimum error criterion via histogram estimation of the densities-classifies using the minimum error criterio n via histogram estimation of the densities
maxlike
- Classify using the maximum-likelyhood algorithm-classifies using the maximum - likelihood al gorithm
min-spantree
- Reduce the number of data points using a spanning tr-Reduce the number of data points using a spa nning tr