FP算法 由韩家炜教授发明 用于挖掘频繁项集

基于Fisher准则线性分类器设计，理解Fisher准则方法确定最佳线性分界面方法的原理，以及Lagrande乘子求解的原理。-Based on Fisher linear classifier design guidelines, understanding the criteria Fisher method to determine the best linear method of the principle of the interface, as well as solving Lagrande multiplier principle.

快速度训练感知机算法，针对线性不可分情况，加快了其收敛速度。-Fast-degree training perceptron algorithm for linear indivisible and speed up its convergence speed.

神经网络的算法，关于BP网络的编写-neural network algorithm, on the preparation of BP Network

仿真1：首先把网络温度参数T固定在100，按工作规则共进行1000次状态更新,把这1000次状态转移中网络中的各个状态出现的次数Si（i＝1，2，…，16）记录下来 按下式计算各个状态出现的实际频率： Pi=Si/∑i=1,NSi=Si/M 同时按照Bo1tzmann分布计算网络各个状态出现概率的理论值： Q（Ei）=（1/Z）exp（-Ei/T） 仿真2：实施降温方案，重新计算 采用快速降温方案：T（t）= T0/（1+t） T从1000降到0.01，按工作规则更新网络状态 当T=0.01时结束降温，再让T保持在0.01进行1000次状态转移，比较两种概率-a simulation : First of all network parameters temperature T fixed at 100 and, according to the rules for a total of 1000 to update the state, this state of the 1000 network transfer of all states for the number of Si (i = 1, 2, ..., 16) all recorded determined by the formula state-of the actual frequency : Pi = Si/i = 1, NSi = Si/M in accordance with Bo1tzmann distributed computing network of states all probability the theoretical value : Q (Ei) = (1/Z) exp (- Ei/T) Simulation 2 : implementation of cooling, re-using rapid cooling programs : T (t) = T0/(1 t) T dropped to 0.01 from 1000 and, according to the rules updated network state when T = 0.01 at the end of cooling, let T at 0.01 for the 1000 state tran

研究机器人控制不可多得资料，强烈推荐-robot control study rare, strongly recommended!

模糊控制逻辑飞机着陆问题算法的vc编程实现-Fuzzy logic control of the aircraft landing problem vc Programming Algorithm

经典的K均值分类算法源码，修正了原作者没有处理当类中样本为0的情况下的bug-classic K-mean classification algorithm source code, that the original author did not address when the category 0 samples of the bug

Lin-Kernighan heuristic for the TSP and minimum weight perfect matching

The Netlab toolbox is designed to provide the central tools necessary for the simulation of theoretically well founded neural network algorithms and related models for use in teaching, research and applications development. It contains many techniques which are not yet available in standard neural network simulation packages-The toolbox is designed to provide t he central tools necessary for the simulation o f theoretically well founded neural network al gorithms and related models for use in teaching , research and applications development. It c ontains many techniques which are not yet avail able in standard neural network simulation pac kages

FastICA算法,使用matlab语言,是非常好的独立成分分析工具.-Fast algorithm, using Matlab language, is a very good independent component analysis tools.