搜索资源列表
filter
- 这里的7个源代码都是关于自适应噪声滤除技术的,其中包括小波分析,LMS,RLS,NLMS自适应滤波器,前向神经网络,BP神经网络自适应除噪-here seven of the source code are adaptive noise filtering technologies, including wavelet analysis, LMS, RLS, NLMS adaptive filter, to the neural network, BP neural network adapti
matlab
- 该算法在优化方面性能比较好,可用于函数极值,解方程,并且在前向神经网络权值和网络结构的训练也表现了不错的性能
bp2
- 前向反馈BP神经网络算法matlab源程序,有详细的注释,是学习编写程序的基本例程。
BP
- 几种前向神经网络的应用实例,用matlab编的源代码
44
- BP算法是为了解决多层前向神经网络的权系数优化而提出来的;所以,BP算法也通常暗示着神经网络的拓扑结构是一种无反馈的多层前向网络-BP algorithm is to solve the multi-layer feedforward neural network weights optimization and put forward Therefore, BP algorithm usually implies that the topology of neural network is
ebp1
- matlab动量梯度下降算法 生成一个新的前向神经网络 对BP神经网络进行训练 对BP神经网络进行仿真-Momentum matlab gradient descent algorithm to generate a new feed-forward neural networks trained BP neural network on the BP neural network simulation
BP-network-for-training
- 利用BP神经网络来训练模型,并用来分类,这个是比较典型的前向型神经网络-BP network for training
BP-neural-network
- BP前向神经网络预测股指走势 (源码) 神经网络训练过程 神经网络模拟曲线,盈利状况与回撤 -BP predict stock movements before (source) to the neural network Neural network training process Neural network simulation curve, profitability and retracement
filter
- 7个源代码都是关于自适应噪声滤除技术的,其中包括小波分析,LMS,RLS,NLMS自适应滤波器,前向神经网络,BP神经网络自适应除噪-here seven of the source code are adaptive noise filtering technologies, including wavelet analysis, LMS, RLS, NLMS adaptive filter, to the neural network, BP neural network adaptive
NNC-matlab
- MATLAB编写的几个神经网络控制器的简单历程,包括感应机、前向网络等。-Several neural network controller to write a simple process of MATLAB, including the induction machine, forward networks.
bin
- 一个采用MATLAB编写的前向反馈性BP神经网络预测3D彩票的例子,不很准确。-A former MATLAB prepared using the feedback of BP neural network 3D lottery example, is not very accurate.
DVMS_V4.0
- rbf神经网络例代码,供参考, RBF网络的结构与多层前向网络类似,它是一种三层前向网络。输入层由信号源结点组成;第二层为隐含层,隐单元数视所描述问题的需要而定,隐单元的变换函数是RBF径向基函数-RBF neural network example code, for your reference
moshi0
- bp神经网络,做浓度反演,机器学习,前向反馈(BP neural network for concentration inversion)
Deep Neural Network
- 深度神经网络训练过程中:首先是进行初始化,根据需求设置神经网络的基本结构;然后进行前向传递(feedforward),层与层之间进行传递,求得误差;然后进行反向传播(back propogation),根据误差最小化原则,使用随机梯度下降法,对各个参数进行求导,确定下降方向,对各个参数进行更新(In the training process of deep neural network, firstly, initialization is carried out, and the basic