Literature DB >> 18267874

Training feedforward networks with the Marquardt algorithm.

M T Hagan, M B Menhaj.   

Abstract

The Marquardt algorithm for nonlinear least squares is presented and is incorporated into the backpropagation algorithm for training feedforward neural networks. The algorithm is tested on several function approximation problems, and is compared with a conjugate gradient algorithm and a variable learning rate algorithm. It is found that the Marquardt algorithm is much more efficient than either of the other techniques when the network contains no more than a few hundred weights.

Year:  1994        PMID: 18267874     DOI: 10.1109/72.329697

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw        ISSN: 1045-9227


  161 in total

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2.  In silico rationalization of the structural and physicochemical requirements for photobiological activity in angelicine derivatives and their heteroanalogues.

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Journal:  J Comput Aided Mol Des       Date:  2003-01       Impact factor: 3.686

3.  Impact of descriptor vector scaling on the classification of drugs and nondrugs with artificial neural networks.

Authors:  Alireza Givehchi; Gisbert Schneider
Journal:  J Mol Model       Date:  2004-04-06       Impact factor: 1.810

4.  Recurrent neural networks for diagnosis of carpal tunnel syndrome using electrophysiologic findings.

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Journal:  J Med Syst       Date:  2009-04-01       Impact factor: 4.460

5.  A study on hepatitis disease diagnosis using multilayer neural network with levenberg marquardt training algorithm.

Authors:  M Serdar Bascil; Feyzullah Temurtas
Journal:  J Med Syst       Date:  2009-10-16       Impact factor: 4.460

6.  Automated retrieval of CT images of liver lesions on the basis of image similarity: method and preliminary results.

Authors:  Sandy A Napel; Christopher F Beaulieu; Cesar Rodriguez; Jingyu Cui; Jiajing Xu; Ankit Gupta; Daniel Korenblum; Hayit Greenspan; Yongjun Ma; Daniel L Rubin
Journal:  Radiology       Date:  2010-05-26       Impact factor: 11.105

7.  Center of mass acceleration feedback control for standing by functional neuromuscular stimulation: a simulation study.

Authors:  Raviraj Nataraj; Musa L Audu; Robert F Kirsch; Ronald J Triolo
Journal:  J Rehabil Res Dev       Date:  2012

8.  Tuberculosis disease diagnosis using artificial neural networks.

Authors:  Orhan Er; Feyzullah Temurtas; A Cetin Tanrikulu
Journal:  J Med Syst       Date:  2010-06       Impact factor: 4.460

9.  Determination and mapping the spatial distribution of radioactivity of natural spring water in the Eastern Black Sea Region by using artificial neural network method.

Authors:  Cafer Mert Yeşilkanat; Yaşar Kobya
Journal:  Environ Monit Assess       Date:  2015-08-27       Impact factor: 2.513

10.  A radial basis function neural network model for classification of epilepsy using EEG signals.

Authors:  Kezban Aslan; Hacer Bozdemir; Cenk Sahin; Seyfettin Noyan Oğulata; Rizvan Erol
Journal:  J Med Syst       Date:  2008-10       Impact factor: 4.460

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