LinPacker是一个优化矩形布局的工具，是在具有遗传算法的半无限大小区完成这一操作的。对缩减工厂的库存是有用的。...

java的神经网络工具箱-java nerve network toolbox

This directory contains utility for implementing generic Reqursive Least Squares (RLS) algorithm. The example shows how one can use the utility to estamate the parameters of a simple linear discrete time system.

--- -一个介绍支持向量机的文档。 认真读一读，会有收获的。-------- introduced a Support Vector Machine documents. Seriously read, there will be rewarding.

一种数据聚类算法的源码，可以在模式识别和图像处理中试用。 -a data clustering algorithm source code, in pattern recognition and image processing trial.

SOBI算法，采用二阶统计量进行盲分离。-SOBI algorithm, using second-order statistic for blind separation.

基于梯度法编写的RBF神经网络程序，实现对输入数据的逼近-Gradient method based on the preparation process of the RBF neural network to achieve the approximation of the input data

用Canny算子检测图像的边缘 P0404：图像的阈值分割 P0405：用水线阈值法分割图像 P0406：对矩阵进行四叉树分解 P0407：将图像分为文字和非文字的两个类别 P0408：形态学梯度检测二值图像的边缘 P0409：形态学实例――从PCB图像中删除所有电流线，仅保留芯片对象-with Canny operator to detect the edges in the image P0404 : image thresholding segmentation P0405 : water line threshold method image segmentation P0406 : matrix Quadtree P0407 : images into text and non-text of the two categories P0408 : morphological gradient detection Binary Image Edge P0409 : morphology example-- Images from the PCB to delete all current lines, retaining only chip targets

基于粒子滤波原理，选取纹理特征对目标进行描述，实现视频目标的跟踪。-Principle-based particle filter, select the texture features to describe on the target to achieve the objectives of tracking video.

遗传算法应用-Application of genetic algorithms

K-均值聚类算法的编程实现。包括逐点聚类和批处理聚类。K－均值聚类的的时间复杂度是n*k*m，其中n为样本数，k为类别数，m为样本维数。这个时间复杂度是相当客观的。因为如果用每秒10亿次的计算机对50个样本采用穷举法分两类，寻找最优，列举一遍约66.7天，分成3类，则要约3500万年。针对算法局部最优的缺点，本人正在编制模拟退火程序进行改进。希望及早奉给大家，倾听高手教诲。-K-means clustering algorithm programming. Point by point, including clustering and clustering batch. K-means clustering of the time complexity of n* k* m, n samples, several types of k, m sample dimension. The time complexity is a very objective. Because if we use one billion times per second the computer using 50 samples of two exhaustive method to find the optimal set out again about 66.7 days, divided into three categories, offering 3,500 years. Local optimal algorithm against the shortcomings, I was prepared simulated annealing process improvements. Early Feng hope for everyone, listen to the master teachings.