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[Other resource] rbfn DL : 0: 利用MATLAB对神经网络进行编程,用newff()创建两层前向网络。网络输入范围[-1 1]，第一层有10个tansig神经元-using MATLAB right neural network programming with newff () to the creation of a two-tier network. Network input range [-1 1], the first layer 10 tansig neurons
Update : 2008-10-13 Size : 4.83kb Publisher : 龙海侠
[AI-NN-PR] rbfn DL : 0: 利用MATLAB对神经网络进行编程,用newff()创建两层前向网络。网络输入范围[-1 1]，第一层有10个tansig神经元-using MATLAB right neural network programming with newff () to the creation of a two-tier network. Network input range [-1 1], the first layer 10 tansig neurons
Update : 2025-02-19 Size : 5kb Publisher : 龙海侠
[AI-NN-PR] BpNlayerEXE DL : 0: BP神经网络程序，其中包括BP网络的源代码，及全部内容-BP neural network programming, including BP network of source code, and all the contents
Update : 2025-02-19 Size : 5.64mb Publisher : 李欣龙
[Other] bp2 DL : 0: bp神经网络源码, NEWFF---生成一个新的前向神经网络 TRAIN-----对BP神经网络进行训练 SIM----对BP神经网络进行仿真 -bp neural network source code
Update : 2025-02-19 Size : 1kb Publisher : yuanru
[AI-NN-PR] MLPNetworksimulation DL : 0: Matlab 下 BP 神经网络的举例及详细说明。美国大学的一个实验。虽然是 PDF文件，但程序可以直接粘贴下来运行。-The process to train and test a designed MLP neural network : 1) We make training patterns and test patterns. 2) A network architecture should be defined by newff MATLAB function with the number of layers, neurons and transfer functions. 3) The defined neural network architecture is trained by train MATLAB function with input patterns and training parameters. 4) We can easily check the result by using a sim MATLAB function.
Update : 2025-02-19 Size : 98kb Publisher : zhulz
[AI-NN-PR] MATLABandB DL : 0: Matlab中BP神经网络的构建和初始化训练前馈网络的第一步是建立网络对象。函数newff建立一个可训练的前馈网络。这需要4个输入参数。第一个参数是一个Rx2的矩阵以定义R个输入向量的最小值和最大值。第二个参数是一个颟顸每层神经元个数的数组。第三个参数是包含每层用到的转移函数名称的细胞数组。最后一个参数是用到的训练函数的名称。 -matlab bp
Update : 2025-02-19 Size : 238kb Publisher : douzi
[Mathimatics-Numerical algorithms] MY_newff DL : 0: matlab训练神经网络的源代码程序，用于神经网络的学习-matlab neural network training process the source code for the neural network learning
Update : 2025-02-19 Size : 1kb Publisher : jiangnian
[Other] BP DL : 0: bp网络图像分类能运行，针对不同的图片稍作调试即刻。-bpnet
Update : 2025-02-19 Size : 1kb Publisher : wujun
[matlab] BPNN4_2 DL : 0: 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,{ tansig , purelin }, trainlm )
Update : 2025-02-19 Size : 1kb Publisher : 鄭又豪
[Other] yu-2 DL : 0: Update : 2025-02-19 Size : 1kb Publisher : 于洁
[matlab] shenjingwangluo DL : 0: 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 ) 训练次数为1000，训练目标为0.01，学习速率为0.1 net.trainParam.epochs=1000 net.trainParam.goal=0.01 LP.lr=0.1 net = train(net,P,T) 测试数据，和训练数据不一致 P_test=[0.2101 0.0950 0.1298 0.1359 0.2601 0.1001 0.0753 0.0890 0.0389 0.1451 0.0128 0.1590 0.2452 0.0512 0.1319 0.2593 0.1800 0.0711 0.2801 0.1501 0.1298 0.1001 0.1891 0.2531 0.0875 0.0058 0.1803 0.0992 0.0802 0.1002 -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] ' of the maximum and minimum input vector 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' ) training times for the 1000 target of 0.01 training, learning rate of 0.1 net.trainParam.epochs = 1000 net. trainParam.goal = 0.01 LP.lr = 0.1 net = train (net, P, T) test data, and training data inconsistencies P_test = [0.2101 0.0950 0.1298 0.1359 0.2601 0.1001 0.0753 0.0890 0.0389 0.1451 0.0128 0.1590 0.2452 0.0512 0.1319 0.2593 0.1800 0.0711 0.2801 0.1501 0.1298 0.1001 0.1891 0.2531 0.0875 0.0058 0.1803 0.0992 0.0802 0.1002
Update : 2025-02-19 Size : 1kb Publisher : 王飞
[matlab] newff DL : 0: feed forward back propagation neural network-feed forward back propagation neural network
Update : 2025-02-19 Size : 3kb Publisher : ali
[matlab] ann_newff DL : 0: this code is matlab and use newff to create ann.
Update : 2025-02-19 Size : 1kb Publisher : m
[AI-NN-PR] face-recognitionamatlab-program DL : 0: 人脸识别，基于神经网络，代码很精练。 NEWFF——生成一个新的前向神经网络 TRAIN——对 BP 神经网络进行训练 SIM——对 BP 神经网络进行仿真 - The NEWFF- Generate a new feedforward neural network TRAIN- BP neural network training, the SIM- BP Neural Network Simulation
Update : 2025-02-19 Size : 5.26mb Publisher : 陈德胜
[matlab] gm11 DL : 0: function exp85 clear all p=[0:0.1:1.1] t=[22.4570 26.6012 12.6416 5.9367 6.9265 28.2432 31.5068 37.0166 7.8947 1.0398 12.7095] net=newff([0 1],[5 1],{ tansig purelin }, traingdx , learngdm ) net.trainParam.epochs=2500 net.trainParam.goal=0.001 net.trainParam.show=50 net=train(net,p,t) r=sim(net,p) plot(p,t,p,r, * ) y=sim(net,[1.2]) -function exp85 clear all p=[0:0.1:1.1] t=[22.4570 26.6012 12.6416 5.9367 6.9265 28.2432 31.5068 37.0166 7.8947 1.0398 12.7095] net=newff([0 1],[5 1],{ tansig purelin }, traingdx , learngdm ) net.trainParam.epochs=2500 net.trainParam.goal=0.001 net.trainParam.show=50 net=train(net,p,t) r=sim(net,p) plot(p,t,p,r, * ) y=sim(net,[1.2])
Update : 2025-02-19 Size : 2kb Publisher : reynard
[Other] BP-neural-prediction-program-MATLAB DL : 0: 神经网络预测程序求一用 matlab 编的程序 P=[。。。] 输入 T=[。。。] 输出创建一个新的前向神经网络 net_1=newff(minmax(P),[10,1],{ tansig -BP neural network prediction program with MATLAB
Update : 2025-02-19 Size : 233kb Publisher : 李明
[Education soft system] characterrecognition DL : 0: This the error backpropagation algorithm based character recognition program developed in matlab. The program folder contains the training images of some english alphabets & numerals. & trains the neural network using train command in matlab. The neural network is initialized using newff command. After the simulation, the program recognizes the input character. Accuracy on the provided images is 100 .-This is the error backpropagation algorithm based character recognition program developed in matlab. The program folder contains the training images of some english alphabets & numerals. & trains the neural network using train command in matlab. The neural network is initialized using newff command. After the simulation, the program recognizes the input character. Accuracy on the provided images is 100 .
Update : 2025-02-19 Size : 7.37mb Publisher : manish
[Other] pattern-recognition DL : 0: 自己编的人工神经网络（ANN）单隐层单输出，不是调用函数newff产生的，用于模式识别-Own series of artificial neural network (ANN) single hidden layer single output, instead of calling the function newff generated for pattern recognition
Update : 2025-02-19 Size : 41kb Publisher : 刘
[Program doc] matlab_newff DL : 0: matlab神经网络newff函数用来创建网络，为BP神经网络设置参数-newff is very important of BP.
Update : 2025-02-19 Size : 240kb Publisher : 万物
[AI-NN-PR] newff-with-several-methods DL : 0: feed forward neural network trained using several methods,then efficiency of each method represented at the end
Update : 2025-02-19 Size : 1kb Publisher : Cobaya

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