tanh function

Why should I introduce an activation function?If you don't have to activate the function (actually equivalent to the excitation function is f (x) =x), in this case you each layer of output is a linear function of the upper input, it is easy to

This series of articles by the @yhl_leo produced, reproduced please indicate the source. Article Link: http://blog.csdn.net/yhl_leo/article/details/51736830 Noisy Activation Functions is a new paper on activation function published by

ABS () Seek absolute value ACOs () Seeking the inverse cosine ASIN () Ask for the inverse of the string Atan () Ask for anyway cut ATAN2 () To find the tangent, to

ICML 2016 's article [Noisy Activation Functions] gives the definition of an activation function: The activation function is a map h:r→r and is almost everywhere.The main function of the activation function in neural network is to provide the

Cyclic neural network--Realization Gitbook Reading AddressKnowledge of reading address gradients disappearing and gradient explosions Network recall: In the circular neural network-Introduction, the circular neural network is referred to in the same

Deep Learning Notes (i): Logistic classificationDeep learning Notes (ii): Simple neural network, back propagation algorithm and implementationDeep Learning Notes (iii): activating functions and loss functionsDeep Learning Notes: A Summary of

Before I have been using Theano, the previous five deeplearning related articles are also learning Theano some notes, at that time already feel Theano use up a little trouble, sometimes want to achieve a new structure, it will take a lot of time to

ReLu (rectified Linear Units) activation function paper Reference: Deep Sparse rectifier Neural Networks (interesting one paper) Origin: Traditional activation function, neuron activation frequency study, Sparse activation Traditional sigmoid system

ABS   Prototype: extern int ABS (int x ); Usage: # include Function: calculates the absolute value of integer x. Description: calculation | x |. If X is not negative, X is returned. Otherwise,-X is returned. Example: // Abs. c # Include # Include

1. Introduction to Multilayer PerceptronA multilayer perceptron (MLP) can be seen as a logistic regression, but its input is preceded by a non-linear transformation, so that the data is mapped to a linearly divided space, which we call the hidden