1998
DOI: 10.1016/s0165-1684(97)00201-6
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A homotopy method for training neural networks

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Cited by 4 publications
(1 citation statement)
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“…Scholars have studied on the learning process of artificial neural network: a) The improvement of error function and adaptive adjustment of learning rate (such as method of entropy function [14], conjugate gradient method [15] and simplex method [16] ; b) The use of optimization algorithm and parameter estimation theory in other field such as Kalman Filtering [17], Homotopy theory [18] and orthogonal projection algorithm [19]. There are still other improved algorithms which are designed specifically to overcome local minimum.…”
Section: Weight and Biasmentioning
confidence: 99%
“…Scholars have studied on the learning process of artificial neural network: a) The improvement of error function and adaptive adjustment of learning rate (such as method of entropy function [14], conjugate gradient method [15] and simplex method [16] ; b) The use of optimization algorithm and parameter estimation theory in other field such as Kalman Filtering [17], Homotopy theory [18] and orthogonal projection algorithm [19]. There are still other improved algorithms which are designed specifically to overcome local minimum.…”
Section: Weight and Biasmentioning
confidence: 99%