搜索结果

* Lightweight backpropagation neural network. * This a lightweight library implementating a neural network for use * in C and C++ programs. It is intended for use in applications that * just happen to need a simply neural network and do not want to use * needlessly complex neural network librar ...

neural network utility is a Neural Networks library for the C++ Programmer. It is entirely object oriented and focuses on reducing tedious and confusing problems of programming neural networks. By this I mean that network layers are easily defined. An entire multi-layer network can be created in a f ...

neural network 一个演示原理的代码，便于初学者学习。

k-step ahead predictions determined by simulation of the ％ one-step ahead neural network predictor. For NNARMAX ％ models the residuals are set to zero when calculating the ％ predictions. The predictions are compared to the observed output. ％

Produces a matrix of derivatives of network output w.r.t. ％ each network weight for use in the functions NNPRUNE and NNFPE.

％ Train a two layer neural network with the Levenberg-Marquardt ％ method. ％ ％ If desired, it is possible to use regularization by ％ weight decay. Also pruned (ie. not fully connected) networks can ％ be trained. ％ ％ Given a set of corresponding input-output pairs and an initial ％ network, ％ ...

This function applies the Optimal Brain Surgeon (OBS) strategy for ％ pruning neural network models of dynamic systems. That is networks ％ trained by NNARX, NNOE, NNARMAX1, NNARMAX2, or their recursive ％ counterparts.

Train a two layer neural network with a recursive prediction error ％ algorithm ("recursive Gauss-Newton"). Also pruned (i.e., not fully ％ connected) networks can be trained. ％ ％ The activation functions can either be linear or tanh. The network ％ architecture is defined by the matrix NetDef , w ...

8139 network card linux driver

structure EM算法 bayesian network structure learning