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bp-ann
- 本程序为一个误差向后传播的三层前馈神经网络有指导的学习算法,用户可在文件中设置相应参数.-this program back to an error in transmission feed-forward neural network algorithm for the study guide, users can set up in the document corresponding parameters.
bp.rar
- BP神经网络自适应步长训练算法，采用最小误差法，梯度下降法，自适应调节权值,BP neural network training anaysis, is realized by using error feed back, gradient descent applied updating of synaptic weights
BPPatternRecognition
- MATLAB编写的误差反向传播（BP）神经网络简单分类器。-MATLAB prepared by error back-propagation [BP] neural network classifier easy.
nn
- NN neural network for face recognition supervised feed forward back propagation neural network
programs
- Perceptron LMS Feed Forward Back Propagation Character Recognition
BpTRAINING
- 自适应步长BP神经网络训练算法，采用最小误差和梯度下降法更新权值- BP neural network training anaysis， realized by using error feed back, gradient descent applied updating of synaptic weights
LFSR
- Linar feed back register matlab code... Another matlab routine-Linar feed back register matlab code... Another matlab routine!!!
main.c.tar
- 基于反馈的EDF调度算法的仿真及性能测试程序。为原创，希望能收到一些意见。-Feed-back control EDF scheduler implemented on VxWorks kernel. This is original work for a course project. Hope it would be helpful to you guys.
backprop_algo
- Back propagation Algorithm.3 layer feed forward network
ijrte0206121124
- Abstract-This paper introduces the new concept of Artificial Neural Networks (ANNs) in estimating speed and controlling the separately excited DC motor. The neural control scheme consists of two parts. One is the neural estimator, which is us
harmonics
- it is the test to elevate the matlab skills.please answer this and send me the feed back.it is based on general matlab code implementation.
annbp
- 人工神经网络中的前馈神经网络，反向传播算法，-Artificial neural network feed-forward neural network, back propagation algorithm,
newff
- feed forward back propagation neural network-feed forward back propagation neural network
FFbp
- Training a 3 layers feed forward neural network using back propagation algorithm
myBackPropagation
- The principle of back propagation is actually quite easy to understand, even though the maths behind it can look rather daunting. The basic steps are: Initialise the network with small random weights. Present an input pattern to the input la
qam_fb_gardner_symbol_farrow_sync_fb_phase_sync_a
- QAM16. feed-back gardner symbol sync farrow interpolator decision feed-back phase sync gain control .simulink matlab 7.0.
FOC
- 基于simulink的FOC模型，内含电流转速双闭环-simulink FOC model，which include speed and I feed back control