蚁群聚类算法

clustring(Density-Based Spatial Clustering of Applications with Noise) is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jö rg Sander and Xiaowei Xu in 1996.[1] It is a density-based clustering algorithm because it finds a number of clusters starting from the estimated density distribution of corresponding nodes. DBSCAN is one of the most common clustering algorithms and also most cited in scientific literature.

一种基于区域活动轮廓模型，通过引入局部的图像拟合能量来提取图像的局部信息，能够有效的额分割强度不均一的图片。较传统的水平集方法有更少的计算量(By introducing the local image fitting(LIFenergy to extract the local image information,our model is able to segment image with intensity inhomogeneities.)

说明：  HDB3码的编码，图形，功率谱密度。用于通信原理教学等(Code HDB3 coding, graphics, power spectral density. Communication Theory for teaching)

计算正则化模糊神经网络的输出值，分为五层，包括正则化，模糊化和输出层，内有注释。(Output value calculated Regularization Fuzzy Neural Network, is divided into five layers, including regularization, blurring and output layer, within a comment)

matlab code for seemingly unrelated regression

采用matlab语言编写的PR方程计算P-T相图的程序(a program to calculate the P-T plot )

Image Mosaicing interesting application in computer vision

说明：  rule discovery for cancer detection by particle swarm optimization in data mining

人工神经网络基于matlab开发的单层传感器的源程序例子(Artificial neural network matlab-based development model exact type rbf)

这是一个关于GP-ADF和GP-RTSS的工具箱，主要基于“Robust Filtering and Smoothing with Gaussian Processes这篇文章 This software package provides a Matlab implementation of the GP-ADF and the GP-RTSS as described in Marc Peter Deisenroth, Ryan Turner, Marco F. Huber, Uwe D. Hanebeck, Carl Edward Rasmussen: "Robust Filtering and Smoothing with Gaussian Processes" in IEEE Transactions on Automatic Control (2012) The software package also contains implementations of the following filters/smoothers: - GP-ADF/GP-RTSS - Gibbs-filter/Gibbs-RTSS [Deisenroth and Ohlsson, ACC 2011] - EKF/EKS - UKF/URTSS - CKF/CKS We provide a demo script: demo_gprtss.m The code requires MatlabR2007a or newer. (C) Copyright 2012 by Marc Deisenroth   Permission is granted for anyone to copy, use, or modify this software and accompanying documents for any uncommercial purposes