资源列表
akdut
- 用于时频分析算法,计算时间和二维直方图,进行逐步线性回归。- For time-frequency analysis algorithm, Computing time and two-dimensional histogram, Stepwise linear regression.
lunkuoxiandetiqu
- 比较了几种常用的提取轮廓线的算子,例如,sobel算子,roberts算子,log算子等。-Several commonly used operators to extract contour lines are compared, such as Sobel operator, Roberts operator, LOG operator, etc.
RBF网络的回归-非线性函数回归的实现
- 利用RBF神经网络对非线性函数进行回归分析(The nonlinear function is regressed by RBF neural network)
ga_bp
- 转载的遗传算法优化bp网络,运行结果还行。但愿有用。(Reproduced genetic algorithm to optimize the bp network, running the results okay. Hopefully useful.)
SOM神经网络的数据分类--柴油机故障诊断
- 根据燃油压力波的特性,完成柴油机故障诊断分类。(According to the characteristics of the fuel pressure wave, the diesel engine fault diagnosis is completed.)
migong
- 使用Qlearing实现基本的走迷宫游戏(Using Qlearing to achieve maze game)
yaoging
- Genetic algorithms using MATLAB path planning, Constituting the modulated signals of different frequencies, Modern signal processing jobs when the graduate.
shuzhijisuan
- 可以进行弦割计算 ,微分计算,平均值计算,运用迭代法计算,进行二分值计算(String cutting can be calculated, differential calculation, the average value of the calculation, the use of iterative methods for the calculation of two points)
yengfei_v23
- allan FOG output error variance analysis, Chaos-based simulated annealing algorithm, Including the area, perimeter, rectangular, elongation.
chap7
- 通过BP神经网络训练实现分类,将三维的输入转化为固定的二维输出(Through the BP neural network training to achieve classification, the three-dimensional input into a fixed two-dimensional output)
CNN Matlab代码
- 利用大量图像数据对卷积神经网络算法进行训练,通过卷积、池化、下采样以及全连接层训练后的卷积神经网络在图像识别精度越来越高。(By using a large number of image data to train the convolutional neural network algorithm, the accuracy of the image recognition is higher and higher by convolution, pooling, down sampling
神经网络
- 人工神经网络(Artificial Neural Networks,简写为ANNs)是一种模仿动物神经网络行为特征,进行分布式并行信息处理的算法数学模型。这种网络依靠系统的复杂程度,通过调整内部大量节点之间相互连接的关系,从而达到处理信息的目的,并具有自学习和自适应的能力。(Artificial neural network (ANN) is a mathematical model that imitates the behavior characteristics of animal neu
