资源列表
Kohonen
- 该代码为基于Kohonen网络的分类算法，注意归一化处理以及网络的构建-The code for the classification algorithm based on Kohonen networks, pay attention to the normalization processing and network building
f_qujian
- simulink的仿真有两个阶段：一个为初始化，这个阶段主要是设置一些参数，像系统的输入输出个数、状态初值、采样时间等；第二个阶段就是运行阶段，这个 阶段里要进行计算输出、更新离散状态、计算连续状态等等，这个阶段需要反复运行，直至结束。-simulink simulation has two phases: one for initialization, this stage is mainly to set some parameters, such as the number of i
zhangxiaoyong
- simulink的初始化（包括输入输出个数、状态初值、采样时间等）以及运行。-simulink initialization (including the number of input and output, initial state, the sampling time, etc.) and run.
raodongxinhaochansheng
- 作为电力系统暂态，产生必要的扰动模拟信号用于分析-As a power system transient, resulting in the disturbance necessary for the analysis of analog signals
data_struct-C
- 清华大学的数据结构C语言版本光盘，学习C的数据结构绝对好的资源！-Tsinghua University, the disc version of the C language data structures, learning C data structures is absolutely good resources!
pBEpAEpD7pD6pC6pE5
- 1. 两人在线对弈，界面显示棋盘和已下的棋子。棋盘为3X3网格，棋子落在格子中。用“o”和“X”表示两种棋子； 2. 某方的三个棋子连成一条线即赢；-1 Web-based submission system. 2 user registration function to register the author' s information. 3 authors can upload manuscr ipt. 4 The administrator can check all th
Function-approximation
- 应用神经网络来进行正弦函数的逼近，通过参数的调整，效果会有所变化-Neural network to approximate the sine function by parameter tuning, the effect will vary
Pattern-Recognition
- 通过神经网络原理进行数字识别，根据训练样本的多少，效果会有差别。-Principle of neural network identification numbers, according to the number of training samples, the effect will be different.
GA
- 用matlab实现遗传算法单目标优化问题，迭代次数选取不同，效果不同-Genetic algorithm using matlab to achieve a single objective optimization problem, select a different iterations, different results
adapt2
- 自适应神经网络实现线性预测，参数不同预测效果不同-Adaptive linear prediction neural network, different parameters of different prediction
adapt
- 自适应线性神经网络实现噪声对消，参数选取不同，效果不同-Adaptive linear neural network to achieve noise cancellation, select different parameters, different results
multy-calculator
- 通过输入多元多项式的元数以及多项式相关的系数、指数等信息，实现多元多项式的加减乘运算-Multivariate polynomial by entering the metadata and the associated polynomial coefficient, index and other information, to achieve multi-polynomial addition and subtraction multiplication