Treffer: On-line training of neural networks : A sliding window approach for the levenberg-marquardt algorithm
Title:
On-line training of neural networks : A sliding window approach for the levenberg-marquardt algorithm
Source:
Artificial intelligence and knowledge engineering applications : a bioinspired approach (Las Palmas, 15-18 June 2005. Part II)Lecture notes in computer science. :577-585
Publisher Information:
Berlin: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 11 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Algorithme rétropropagation, Backpropagation algorithm, Algoritmo retropropagación, Arrêt au plus tôt, Early stopping, Parada mas temprana, Cognition, Cognición, Fenêtre coulissante, Sliding window, Ventana deslizante, Ingénierie connaissances, Knowledge engineering, Intelligence artificielle, Artificial intelligence, Inteligencia artificial, Intervalle confiance, Confidence interval, Intervalo confianza, Méthode itérative, Iterative method, Método iterativo, Procédé discontinu, Batch process, Procedimiento discontínuo, Production par lot, Batch production, Producción por lote, Réseau neuronal, Neural network, Red neuronal
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Escola Superior de Tecnologia de Setúbal do Instituto Politécnico de Setùbal, Departamento de Engenharia Electrotécnica, Campus do IPS, Estefanilha, 2914-508 Setùbal, Portugal
Escola Superior de Tecnologia de Castelo Branco, Departamento de Engenharia Electrotécnica, Av. Empresário, 6000 Castelo Branco, Portugal
Departamento de Electrónica e Telecomunicaçôes, Universidade de Aveiro, 3810 - 193 Aveiro, Portugal
Escola Superior de Tecnologia de Castelo Branco, Departamento de Engenharia Electrotécnica, Av. Empresário, 6000 Castelo Branco, Portugal
Departamento de Electrónica e Telecomunicaçôes, Universidade de Aveiro, 3810 - 193 Aveiro, Portugal
ISSN:
0302-9743
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.17010814
Database:
PASCAL Archive
Weitere Informationen
In the Neural Network universe, the Backpropagation and the Levenberg-Marquardt are the most used algorithms, being almost consensual that the latter is the most effective one. Unfortunately for this algorithm it has not been possible to develop a true iterative version for on-line use due to the necessity to implement the Hessian matrix and compute the trust region. To overcome the difficulties in implementing the iterative version, a batch sliding window with Early Stopping is proposed, which uses a hybrid Direct/Specialized evaluation procedure. The final solution is tested with a real system.