matlab neural network tutorial

processor can be much faster than other libraries that do not support fixed-point operations.Although FANN is a pure C language, but according to the object-oriented thinking framework, interface design is very good. Have more detailed documentation, easy to use. and has been supported in more than 20 programming language environments, such as C #, JAVA, Delphi, PYTHON, PHP, PERL, RUBY, Javascript, Matlab, R and so on.The following is a very simple e

With the neural network of small partners know that the data needs to be normalized, but why to do normalization, the problem has always been ambiguous, and there is no more than the answer on the net, the small series spent a period of time, made some research, give us a careful analysis, why do normalization: 1. Numerical problems. There is no doubt that normalization can indeed avoid some unnecessary n

://www.cs.toronto.edu /~ Graves/preprinthistory. The development of recurrent neural networks. VanillaRNN-> Enhanced the hidden layer function-> Simple RNN-> GRU-> LSTM-> CW-RNN-> Bidirectional deepening Network-> Bidirectional RNN-> Keep Bidrectional RNN-> Combination of the two: DBLSTMRecurrent Neural Networks, Part 1-Introduction to RNNs http://www.wildml.com/

rate can reach 97% +The above can be UFLDL on the implementation of CNN, the most important thing is to figure out each layer in each process needs to be done, I summarize in the article at the beginning of the table ~matlab give me a big feeling is the matrix of demension match, sometimes know the formula is what kind of, However, to consider the dimensions of the matrix, the two-dimensional match matrix can be multiplied or added, but the benefit i

This chapter does not involve too many neural network principles, but focuses on how to use the Torch7 neural networkFirst require (equivalent to the C language include) NN packet, the packet is a dependency of the neural network, remember to add ";" at the end of the statem

convolutional Neural Network Primer (1) Original address : http://blog.csdn.net/hjimce/article/details/47323463 Author : HJIMCE convolutional Neural Network algorithm is an n-year-old algorithm, only in recent years because of deep learning related algorithms for the training of multi-layered networks to provide a new

A course of recurrent neural Network (1)-RNN Introduction source:http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/ As a popular model, recurrent neural Network (Rnns) has shown great app

Dnns." ARIXV preprint, Arxiv:1608.04493v1, 2016. [3] Yu, Kai. "A tutorial on the deep learning." China Workshop on machine learning and applications, 2012. Lei Feng Network Note: This article by the Deep Learning journal ER authorized Lei Feng Network (search "Lei Feng Network" public attention) released, if

weight is updated with the formula: 6, the offset update offset formula is: Implicit layer-to-output layer offset update Then the offset's update formula is: Bias update for input layer to hidden layer Where the offset of the update formula is: 7, to determine whether the algorithm iteration end there are many ways to determine whether the algorithm has been convergent, the common has a specified iteration of algebra, to determine whether the difference between the a

, we can directly use the full connection of the neural network, to carry out the follow-up of these 120 neurons, the following specific how to do, as long as the knowledge of multi-layer sensors understand, do not explain. The above structure, is only a reference, in the real use, each layer feature map needs how many, volume kernel size selection, as well as the pool when the sample rate to how much, and

Hopfield Neural network usage instructions.There are two characteristics of this neural network:1, output value is only 0, 12,hopfield not entered (input)Here's a second feature, what do you mean no input? Because in the use of Hopfield network, more used for image simulatio

://www.ibm.com/developerworks/cn/java/j-lo-robocode3/index.html Artificial Intelligence Java tank robot series: neural networks, lower Http://www.ibm.com/developerworks/cn/java/j-lo-robocode4/ Constructing a neural network using Python-the CNN can reconstruct distorted patterns and eliminate noise. Http://www.ibm.com/developerworks/cn/linux/l-neurnet/ Provide bas

chooses the S-type tangent function Tansig as the excitation function of the hidden-layer neurons. As the output of the network is within the range of [-1, 1], the predictive model chooses the S-type logarithmic function Tansig as the excitation function of the output layer neuron.Implementation of 4.4.2.2.3 ModelThis prediction selects the Neural Network Toolbo

BP (backward propogation) neural networkSimple to understand, neural network is a high-end fitting technology. There are a lot of tutorials, but in fact, I think it is enough to look at Stanford's relevant learning materials, and there are better translations at home: Introduction to Artificial neural