NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Cascade Back-Propagation Learning in Neural NetworksThe cascade back-propagation (CBP) algorithm is the basis of a conceptual design for accelerating learning in artificial neural networks. The neural networks would be implemented as analog very-large-scale integrated (VLSI) circuits, and circuits to implement the CBP algorithm would be fabricated on the same VLSI circuit chips with the neural networks. Heretofore, artificial neural networks have learned slowly because it has been necessary to train them via software, for lack of a good on-chip learning technique. The CBP algorithm is an on-chip technique that provides for continuous learning in real time. Artificial neural networks are trained by example: A network is presented with training inputs for which the correct outputs are known, and the algorithm strives to adjust the weights of synaptic connections in the network to make the actual outputs approach the correct outputs. The input data are generally divided into three parts. Two of the parts, called the "training" and "cross-validation" sets, respectively, must be such that the corresponding input/output pairs are known. During training, the cross-validation set enables verification of the status of the input-to-output transformation learned by the network to avoid over-learning. The third part of the data, termed the "test" set, consists of the inputs that are required to be transformed into outputs; this set may or may not include the training set and/or the cross-validation set. Proposed neural-network circuitry for on-chip learning would be divided into two distinct networks; one for training and one for validation. Both networks would share the same synaptic weights.
Document ID
20110023823
Document Type
Other - NASA Tech Brief
Authors
Duong, Tuan A. (California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
August 25, 2013
Publication Date
May 1, 2003
Publication Information
Publication: NASA Tech Briefs, May 2003
Subject Category
Man/System Technology and Life Support
Report/Patent Number
NPO-19289
Distribution Limits
Public
Copyright
Public Use Permitted.

Available Downloads

NameType 20110023823.pdf STI

Related Records

IDRelationTitle20110023805Analytic PrimaryNASA Tech Briefs, May 2003