DocumentCode
1031869
Title
Feedback stabilization using two-hidden-layer nets
Author
Sontag, Eduardo D.
Author_Institution
Dept. of Math., Rutgers Univ., New Brunswick, NJ, USA
Volume
3
Issue
6
fYear
1992
fDate
11/1/1992 12:00:00 AM
Firstpage
981
Lastpage
990
Abstract
The representational capabilities of one-hidden-layer and two-hidden-layer nets consisting of feedforward interconnections of linear threshold units are compared. It is remarked that for certain problems two hidden layers are required, contrary to what might be in principle expected from the known approximation theorems. The differences are not based on numerical accuracy or number of units needed, nor on capabilities for feature extraction, but rather on a much more basic classification into direct and inverse problems. The former correspond to the approximation of continuous functions, while the latter are concerned with approximating one-sided inverses of continuous functions, and are often encountered in the context of inverse kinematics determination or in control questions. A general result is given showing that nonlinear control systems can be stabilized using two hidden layers, but not, in general, using just one
Keywords
control system analysis; feedback; feedforward neural nets; inverse problems; nonlinear control systems; stability; feedback stabilisation; feedforward neural nets; inverse kinematics; inverse problems; linear threshold units; nonlinear control systems; stability; two-hidden-layer nets; Control systems; Control theory; Feature extraction; Kinematics; Neural networks; Neurofeedback; Nonlinear control systems; Nonlinear systems; Piecewise linear techniques; State feedback;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.165599
Filename
165599
Link To Document