Add to ORKGThis paper presents some numerical experiments related to a new global "pseudo-backpropagation" algorithm for the optimal learning of feedforward neural networks. The propose
Abstract-The Back-propagation (BP) training algorithm is a renowned representative of all iterative ...
Over the past two decades, the feedforward neural network (FNN) optimization has been a key interest...
Since the presentation of the backpropagation algorithm, a vast variety of improvements of the techn...
This paper presents some numerical experiments related to a new global "pseudo-backpropagation" algo...
A theoretical formulation of a fast learning method based on a pseudoinverse technique is presented....
A backpropagation learning algorithm for feedforward neural networks with an adaptive learning rate ...
In this paper we explore different strategies to guide backpropagation algorithm used for training a...
A backpropagation learning algorithm for feedforward neural networks with an adaptive learning rate ...
The back-propagation algorithm calculates the weight changes of an artificial neural network, and a ...
The training of multilayer perceptron is generally a difficult task. Excessive training times and la...
In studies of neural networks, the Multilavered Feedforward Network is the most widely used network ...
This report contains some remarks about the backpropagation method for neural net learning. We conce...
The problem of computing machine passing the maze is one of theoretical computer science key tasks. ...
This paper deals with the computational aspects of neural networks. Specifically, it is suggested th...
this paper. After evaluating some of these limits, as well as some of the advantages, we present a n...
Abstract-The Back-propagation (BP) training algorithm is a renowned representative of all iterative ...
Over the past two decades, the feedforward neural network (FNN) optimization has been a key interest...
Since the presentation of the backpropagation algorithm, a vast variety of improvements of the techn...
This paper presents some numerical experiments related to a new global "pseudo-backpropagation" algo...
A theoretical formulation of a fast learning method based on a pseudoinverse technique is presented....
A backpropagation learning algorithm for feedforward neural networks with an adaptive learning rate ...
In this paper we explore different strategies to guide backpropagation algorithm used for training a...
A backpropagation learning algorithm for feedforward neural networks with an adaptive learning rate ...
The back-propagation algorithm calculates the weight changes of an artificial neural network, and a ...
The training of multilayer perceptron is generally a difficult task. Excessive training times and la...
In studies of neural networks, the Multilavered Feedforward Network is the most widely used network ...
This report contains some remarks about the backpropagation method for neural net learning. We conce...
The problem of computing machine passing the maze is one of theoretical computer science key tasks. ...
This paper deals with the computational aspects of neural networks. Specifically, it is suggested th...
this paper. After evaluating some of these limits, as well as some of the advantages, we present a n...
Abstract-The Back-propagation (BP) training algorithm is a renowned representative of all iterative ...
Over the past two decades, the feedforward neural network (FNN) optimization has been a key interest...
Since the presentation of the backpropagation algorithm, a vast variety of improvements of the techn...