Application of higher order feedforward neural networks in regional environmental quality assessment;

Multi-layer feedforward neural network based on binary ant colony algorithms;

Chaos BP hybrid learning algorithm for feedforward neural network;

A new feedforward neural network pruning algorithm;

Newton-gradient coupling algorithm for feedforward neural networks;

Computing Lyapunov exponents with feedforward neural networks;

,this paper proposes a new algorithm which combined the advantages of the momentum feedforward neural networks and the traditional CMA blind equalization algorithms,which adjusts the new weight value with the adjusting value used before so that the algorithm could be less sensitive to the stationary point of the error surface.

Application of feed-forward neural networks to dam deformation monitoring based on differential evolution algorithm;

Applied to the problem of optimizing the connection weights of the feed-forward neural networks,the algorithm was feasible.

On the basis of both adaptive BP algorithm and Newton s method, Quasi Newton algorithm with adaptive decoupled step and momentum (QNADSM) for feed-forward neural networks is derived.

Robust maximum likelihood feed forward neural network and its application study;

The characteristic of the feed forward neural network and training algorithm based on the recursive prediction error are introduced.

This text discusses melt sparsely of the feed forward neural network,that is how to determine and delete the network s redundant neuron and joining,gives the mathematics define of feed forward neural network,and introduces the Lean towards preface and Arrange in an order topologically to the Study algorithm and Sparse to take the algorithm of feed forward neural network.