An application of artificial neural networks to experimental data approximationAs an initial step in the evaluation of networks, a feedforward architecture is trained to approximate experimental data by the backpropagation algorithm. Several drawbacks were detected and an alternative learning algorithm was then developed to partially address the drawbacks. This noniterative algorithm has a number of advantages over the backpropagation method and is easily implemented on existing hardware.
Document ID
19930039333
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Meade, Andrew J., Jr. (Rice Univ. Houston, TX, United States)
Date Acquired
August 16, 2013
Publication Date
January 1, 1993
Subject Category
Cybernetics
Report/Patent Number
AIAA PAPER 93-0408
Meeting Information
Meeting: AIAA, Aerospace Sciences Meeting and Exhibit