机器学习 的 课件 ppt格式 对于人工智能有兴趣的同学可以

一个用c++builder实现的神经网络算法的程序-c builder with a realization of the neural network algorithm for the procedure

书籍“Regularization tools for training large feed-forward neural networks using Automatic Differentiation”的源码文件-Books

ADALINE(神经网络 vc＋＋编写的)-ADALINE (neural networks, prepared by vc )

无先导粒子滤波器工具箱，并附带pf，kf，Ukf程序，用于跟踪估计-without leading particle filter toolbox and fringe pf, kf, Ukf procedures for tracking estimates

BP算法C++的BP算法源程序 BP算法C++的BP算法源程序 -BP algorithm C BP algorithm source algorithm C BP BP algorithm source code

使用神经网络的K算法来对数据进行分类，有具体的实验要求和图-K using the neural network algorithm to classify the data, there is a specific test requirements and plans

很好用的一个适用程序，由Visual C＋＋编程，有收藏价值-A very good application of the procedures used by Visual C programming, have value for collection

模拟退火算法 模拟退火算法(Simulated Annealing,简称SA算法)是模拟加热熔化的金属的退火过程，来寻找全局最优解的有效方法之一。 模拟退火的基本思想和步骤如下： 设S＝{s1,s2,…,sn}为所有可能的状态所构成的集合， f：S―R为非负代价函数，即优化问题抽象如下： 寻找s*∈S，使得f(s*)＝min f(si) 任意si∈S （1）给定一较高初始温度T，随机产生初始状态S （2）按一定方式，对当前状态作随机扰动，产生一个新的状态S’ S’＝S＋sign(η).δ 其中δ为给定的步长， η为[－1,1]的随机数-simulated annealing algorithm (Simulated Annealing, or SA algorithm) is a simulation of heating molten metal in the annealing process, to find the global optimum one of the effective ways. Simulated Annealing basic ideas and the steps are as follows : S = (s1, s2, ..., sn) for all possible state posed by the pool, f : S-R non-negative cost function, that is abstract optimization problems are as follows : Find S* s, making f (s*) = min f (si) arbitrary si S (1) to set a higher initial temperature T, randomly generated initial state S (2) of a certain form, the current state of random disturbance, have a new state S "S" = S+ sign (). delta where given for the step, [-1,1] Random Number

基于贝叶斯的数据挖掘算法的实现,使用visual stutio2005编程实现。-Bayesian data mining algorithm, using the visual stutio2005 programming.

神经网络OOP类库，含有BP网络等的训练，很容易对其进行扩展，-neural network OOP libraries, containing BP network of training, it is easy to extend them