Data classification with multilayer perceptrons using a generalized error function

LM Silva, JM de Sá, LA Alexandre - Neural Networks, 2008 - Elsevier
The learning process of a multilayer perceptron requires the optimization of an error function
E (y, t) comparing the predicted output, y, and the observed target, t. We review some usual …
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[引用][C] Data classification with multilayer perceptrons using a generalized error function

LM SILVA, JM DE SA, LA ALEXANDRE - Neural networks, 2008 - pascal-francis.inist.fr
Data classification with multilayer perceptrons using a generalized error function CNRS Inist
Pascal-Francis CNRS Pascal and Francis Bibliographic Databases Simple search Advanced …

Data classification with multilayer perceptrons using a generalized error function

LM Silva, JM de Sá… - Neural networks: the …, 2008 - pubmed.ncbi.nlm.nih.gov
The learning process of a multilayer perceptron requires the optimization of an error function
E (y, t) comparing the predicted output, y, and the observed target, t. We review some usual …
[PDF] psu.edu

[PDF][PDF] Data classification with multilayer perceptrons using a generalized error function

LM Silva, JM de Sá, LA Alexandre - Neural Networks, 2008 - Citeseer
abstract The learning process of a multilayer perceptron requires the optimization of an error
function E (y, t) comparing the predicted output, y, and the observed target, t. We review …
[PDF] up.pt

[PDF][PDF] Data classification with multilayer perceptrons using a generalized error function

LM Silva, JM de Sá, LA Alexandre - Neural Networks, 2008 - deepnets.ineb.up.pt
abstract The learning process of a multilayer perceptron requires the optimization of an error
function E (y, t) comparing the predicted output, y, and the observed target, t. We review …
[PDF] ubi.pt

[PDF][PDF] Data classification with multilayer perceptrons using a generalized error function

LM Silva, JM de Sá, LA Alexandre - Neural Networks, 2008 - di.ubi.pt
abstract The learning process of a multilayer perceptron requires the optimization of an error
function E (y, t) comparing the predicted output, y, and the observed target, t. We review …

Data classification with multilayer perceptrons using a generalized error function

LM Silva, JM de Sá, LA Alexandre - Neural Networks, 2008 - infona.pl
The learning process of a multilayer perceptron requires the optimization of an error function
E (y, t) comparing the predicted output, y, and the observed target, t. We review some usual …

Data classification with multilayer perceptrons using a generalized error function.

LM Silva, J Marques de Sá… - Neural Networks: the …, 2008 - europepmc.org
The learning process of a multilayer perceptron requires the optimization of an error function
E (y, t) comparing the predicted output, y, and the observed target, t. We review some usual …

Data classification with multilayer perceptrons using a generalized error function

LM Silva, J Marques de Sá, LA Alexandre - Neural Networks, 2008 - dl.acm.org
The learning process of a multilayer perceptron requires the optimization of an error function
E (y, t) comparing the predicted output, y, and the observed target, t. We review some usual …
[PDF] ubi.pt

[PDF][PDF] Data classification with multilayer perceptrons using a generalized error function

LM Silva, JM de Sá, LA Alexandre - Neural Networks, 2008 - di.ubi.pt
abstract The learning process of a multilayer perceptron requires the optimization of an error
function E (y, t) comparing the predicted output, y, and the observed target, t. We review …