Stability of steepest descent with momentum for quadratic functions

This paper analyzes the effect of momentum on steepest descent training for quadratic performance functions. We demonstrate that there always exists a momentum coefficient that will stabilize the steepest descent algorithm, regardless of the value of the learning rate. We also demonstrate how the va...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2002-05, Vol.13 (3), p.752-756
Hauptverfasser:	Torii, M., Hagan, M.T.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithm design and analysis Algorithms Backpropagation algorithms Coefficients Convergence Cost function Descent Eigenvalues and eigenfunctions Equations Learning Neural networks Performance analysis Stability Symmetric matrices Training
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