Title :
Feedback stabilization using two-hidden-layer nets
Author :
Sontag, Eduardo D.
Author_Institution :
Dept. of Math., Rutgers Univ., New Brunswick, NJ, USA
fDate :
11/1/1992 12:00:00 AM
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;
Journal_Title :
Neural Networks, IEEE Transactions on