spiking neural network book

Original address: http://www.sohu.com/a/198477100_633698 The text extracts from the vernacular depth study and TensorFlow With the continuous research and attempt on neural network technology, many new network structures or models are born every year. Most of these models have the characteristics of classical neural

training set, and the network still has a great chance of recognizing it. It is this generalization that makes the neural network a priceless tool that can be used in countless applications, from face recognition, medical diagnostics, to racing predictions, there is also the navigation of bots in computer games (robots that act as game characters) or hardware ro

"Matlab Neural network Programming" Chemical Industry Press book notesFourth. Forward-type neural network 4.2 linear neural network This article is "MATLAB

P1038 neural network and p1038 Neural NetworkBackground Artificial Neural Network (Artificial Neural Network) is a new computing system with self-learning ability. It is widely used in

Tips: This article is a reference to the mechanical industry press "neural network Design" (Dai Qu, etc.) a book compiled by the relevant procedures, for beginners or want to learn more about the neural network kernel enthusiasts, this is the most reading value of the textbo

Currently, Java is used to develop the largest number of ape programs, but most of them are limited to years of development. In fact, Java can do more and more powerful! I used Java to build a [self-built neural network] instead of laboratory work, it is a real, direct application that makes our programs smarter, let our program have the perception or cognitive function! Do not use the same number as the

Source: Michael Nielsen's "Neural Network and Deep leraning"This section translator: Hit Scir master Xu Zixiang (Https://github.com/endyul)Disclaimer: We will not periodically serialize the Chinese translation of the book, if you need to reprint please contact [email protected], without authorization shall not be reproduced."This article is reproduced from" hit S

network prediction Total number of layers $L $-neural network (including input and output layers) $\theta^{(L)}$-the weight matrix of the $l$ layer to the $l+1$ layer $s _l$-the number of neurons in the $l$ layer, note that $i$ counts from 1, and the weights of bias neurons are not counted in the regular term. The number of neurons in the _{l+1}$

introduces the latter.1958 Rosenblatt presented the Perceptron (Perceptron), which is essentially a linear classifier, 1969 Minsky and Papert wrote a book "Perceptrons", which they pointed out in the book: ① Single-layer perceptron can not achieve XOR function, ② computer ability is limited, can not deal with the long-running process of neural

really simple, very mathematical beauty. Of course, as a popular science books, it will not tell you how harmful this method is.Implementation, you can use the following two algorithms:①KMP: Put $w_{i}$, $W _{i-1}$ two words together, run once the text string.②ac automaton: Same stitching, but pre-spell all the pattern string, input AC automaton, just run once text string.But if you are an ACM player, you should have a deep understanding of the AC automaton, which is simply a memory killer.The

Reprint please indicate the Source: Bin column, Http://blog.csdn.net/xbinworldThis is the essence of the whole fifth chapter, will focus on the training method of neural networks-reverse propagation algorithm (BACKPROPAGATION,BP), the algorithm proposed to now nearly 30 years time has not changed, is extremely classic. It is also one of the cornerstones of deep learning. Still the same, the following basic reading notes (sentence translation + their o

This is the essence of the whole fifth chapter, will focus on the training method of neural networks-reverse propagation algorithm (BACKPROPAGATION,BP), the algorithm proposed to now nearly 30 years time has not changed, is extremely classic. It is also one of the cornerstones of deep learning. Still the same, the following basic reading notes (sentence translation + their own understanding), the contents of the b