资源列表
iris_analysis
- 分类算法将Iris分为三种类型(Setosa, Versicolour, Virginica),找出特征属性占比较大的几个属性，然后对数据进行降维以便于聚类分析，最终将数据分类。(The classification algorithm divides Iris into three types (Setosa, Versicolour, Virginica) to find a few attributes of characteristic attributes, and then redu
GA algothrim
- 模拟达尔文生物进化理论和遗传学机理实现了遗传算法(the running process of genetic algorithm)
fdtd
- 实现一个Fdtd的二维算法，模拟电磁场的发散过程(A two-dimensional algorithm of Fdtd is implemented to simulate the divergence process of electromagnetic field.)
2
- 一维可压缩黏性流动问题的数值解法与计算程序，一维可压缩黏性流动是气体动力学中最经典的黏性流动问题，对它采用迎风型差分算法进行数值求解。(The numerical solution and calculation program of one-dimensional compressible viscous flow problem, the one-dimensional compressible viscous flow is the most classical viscous flow
neural networks
- 1.elman神经网络对输入波形进行检测 2.设计具有3个神经元的Hopfield网络 3.建立自适应神经模糊推理系统对非线性函数进行逼近（正弦加滞后） 4.建立自适应神经模糊推理系统对非线性函数进行逼近（正弦多项式） 5.利用模糊C均值聚类方法将一类随机给定的三维数据分为三类(1.Detection of input waveform by elman neural network 2. design a Hopfield network with 3 neurons 3. est
MATLAB实现鸢尾花数据集分类
- 基于BP算法的鸢尾花数据集分类，在MATLAB平台下编程实现BP算法，可计算识别率。(Based on the BP algorithm, iris data set is classified. Under the MATLAB platform, the BP algorithm is programmed and the recognition rate can be calculated.)
python小程序
- 根据传统的经典迪杰特斯拉算法，利用Python求解最短路径(shortest path.According to the traditional classic detesla algorithm, we use Python to solve the shortest path.)
matlab贝叶斯分类(1)-简单样本集
- 利用matlab实现贝叶斯分类，采取“留一法”选取训练集和测试集，最后返回准确率为0.8571。(Bias classification is realized by MATLAB, and training set and test set are selected by "leaving one method", and the accuracy of return is 0.8571.)
mrt
- 采用格子Boltzmann方法的mrt模拟顶盖驱动流(MRT simulation of lid driven flow using lattice Boltzmann method)
W124-PCA和LDA人脸识别
- 实现人脸的识别，使用LDA的模型，基于matlab的语言(Realize face recognition)
stable
- 信号处理中，生成alpha稳定分布脉冲噪声的程序，可以用作阵列信号处理的噪声环境仿真。(In signal processing, the program that generates alpha stable distributed impulse noise can be used to simulate the noise environment of array signal processing.)
Q-learning
- 强化学习的核心算法，Q-table，应用动作值函数对动作的Q值进行更新来找到最优策略。(The core algorithm of reinforcement learning, Q-table, uses action value function to update the Q value of actions to find the optimal strategy.)