搜索资源列表
BPBPzui
- 通过在MATLAB平台上比较BP神经网络的三种训练方法-trainbr traingdm trainlm.并且网络中加入噪音!-through MATLAB platform comparison BP neural network training method for the three-trainbr traingdm trainlm. Network and add noise!
11
- L-M优化算法(trainlm)和贝叶斯正则化算法(trainbr)
bayes_bpnet
- 采用贝叶斯正则化算法提高 BP 网络的推广能力。我们采用两种训练方法,即 L-M 优化算法(trainlm)
BPBPzui
- 通过在MATLAB平台上比较BP神经网络的三种训练方法-trainbr traingdm trainlm.并且网络中加入噪音!-through MATLAB platform comparison BP neural network training method for the three-trainbr traingdm trainlm. Network and add noise!
11
- L-M优化算法(trainlm)和贝叶斯正则化算法(trainbr)-LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr)
bayes_bpnet
- 采用贝叶斯正则化算法提高 BP 网络的推广能力。我们采用两种训练方法,即 L-M 优化算法(trainlm)-?捎??
bp.example
- 采用动量梯度下降算法训练BP网络,采用两种训练方法,即 L-M 优化算法(trainlm)和贝叶斯正则化算法(trainbr),用以训练 BP 网络-Gradient descent algorithm using momentum BP network training, using two training methods, namely, LM optimization algorithm (trainlm) and Bayesi
bys
- 采用贝叶斯正则化算法提高BP网络的推广能力。在本例中,将采用两种训练方法,即L-M优化算法(trainlm)和贝叶斯正则化算法(trainbr),用以训练BP网络,使其能够拟合某一附加有白噪声的正弦样本数据。-The use of Bayesian regularization algorithm for BP network to improve generalization ability. In this case, two ty
exampls
- This file contains examples of training by using trainlm algorthim
BPNN4_2
- load training.txt load TrainOut.txt load validation.txt load ValOut.txt load testing.txt load TestOut.txt INPUT=[training validation testing] OUTPUT=[TrainOut ValOut TestOut] net=newff(INPUT,OUTPUT,200,{ t
trainlm
- 采用两种训练方法,即 L-M 优化算法(trainlm)和贝叶斯正则化算法(trainbr)-Using two training methods, namely, LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr)
BPcode
- matlab模拟BP网络,使用trainlm和traingd以及traingdx传递函数。-matlab simulation of BP network, the use of trainlm and traingd and traingdx transfer function.
shenjingwangluo
- T=[1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1] 输入向量的最大值和最小值 threshold=[0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1] net=newff(threshold,[31 3],{ tansig , logsig }, trainlm )
Example4
- 采用贝叶斯正则化算法(抑制过拟合)提高 BP 网络的推广能力,采用两种训练方法, 即 L-M 优化算法(trainlm)和贝叶斯正则化算法(trainbr),用以训练 BP 网络;-Bayesian regularization algorithm (inhibition of over-fitting) to improve the generalization ability of BP network, using two
trainlm
- 使用MATLAB语言写的,LM算法,将LM算法应用于神经网络的训练,大幅提高速度-Using MATLAB language, LM algorithm
biansulvshenjingwangluo
- 变速率的神经网络matlab程序,采trainlm 函数-Variable rate of neural networks matlab program, the mining trainlm function
Bayes-in-BP(code)
- 采用贝叶斯正则化算法提高 BP 网络的推广能力。在本例中,我们采用两种训练方法,即 L-M 优化算法(trainlm)和贝叶斯正 则化算法(trainbr),用以训练 BP 网络,使其能够拟合某一附加有白噪声的正弦样本数据。-Use Bayes to train BP network
twodimapproximationbp
- 单输出函数Y=SIN(X)逼近问题的bp程序:假设网络结构为3--2--1,输入维数M,共N个样本,一般输入不算层,输出算层- 激活函数: hardlim---(0,1),hardlims---(-1,1),purelin,logsig---(0,1),tansig----(-1,1) softmax,poslin,radbas,satlin,satlins,tribas 训练算法: 1.traing
Bayesian-regularization
- 贝叶斯正则化算法提高 BP 网络,L-M 优化算法(trainlm)和贝叶斯正则化算法(trainbr),用以训练 BP 网络-Bayesian regularization algorithm to improve BP network
BP_futures
- 【神经网络BP预测期货收盘价】:用开盘价、最高价、最低价、收盘价数据预测未来几天的收盘价,训练方法为trainlm。数据只需要一个txt文件,可以自己网上下载,TB或文化软件提取,本人提供了一份txt的开高低收文件。-[BP neural network to predict futures closing price]: with open, high, low, close price data to predict the clo