adp

用蒙特卡罗法求解ising模型，并包括相关的文献。(Ising method using Monte Carlo models, and includes the relevant literature.)

说明：  自学的必备工具之一,通过编程可以练习进行各种生产单位的实践工作(Self taught one of the necessary tools)

基于朴素贝叶斯的分类练习，在UCI数据库中的breast数据集上进行的测试(Bayesian classification based on practice, in the UCI database data set on breast test)

在Matlab中实现基于旋转尺度不变特征提取特征点的方法。(Matlab implementation of the rotation based on scale-invariant feature extraction method of feature points.)

说明：  一个非常不错的PLSLDA工具包 内附有详细的中文帮助 使用简单 功能强大(PLSLDA a very good kit containing a detailed easy to use and powerful Chinese help)

wave cluster for biomedical signal proce

这是组合一个优化算法GABP，很好的提高BP预测精度(It is a combination of an optimization algorithm GABP, good way to improve the prediction accuracy of BP)

说明：  遗传算法是计算数学中用于解决最佳化的搜索算法，是进化算法的一种。进化算法最初是借鉴了进化生物学中的一些现象而发展起来的，这些现象包括遗传、突变、自然选择以及杂交等。遗传算法通常实现方式为一种计算机模拟。对于一个最优化问题，一定数量的候选解（称为个体）的抽象表示（称为染色体）的种群向更好的解进化。传统上，解用二进制表示（即0和1的串），但也可以用其他表示方法。进化从完全随机个体的种群开始，之后一代一代发生。在每一代中，整个种群的适应度被评价，从当前种群中随机地选择多个个体（基于它们的适应度），通过自然选择和突变产生新的生命种群，该种群在算法的下一次迭代中成为当前种群。(Genetic algorithm (GA) is a search algorithm used to solve optimization in computational mathematics. It is one of evolutionary algorithms. Evolutionary algorithms were originally developed by borrowing phenomena in evolutionary biology, such as heredity, mutation, natural selection and hybridization. Genetic algorithms are usually implemented as a computer simulation. For an optimization problem, an abstract representation of a certain number of candidate solutions (called individuals) (called chromosomes) evolves towards a better solution. Traditionally, solutions are represented in binary (that is, strings of zeros and ones), but other representations are possible. Evolution begins with a population of completely random individuals, and it happens from generation to generation.)

The Matlab Toolbox for Pattern Recognition

matlab + 最短路径 改进的蚁群算法(matlab+ improved ant colony algorithm for the shortest path)