1. A learning approximator for compact representation of experimental mappings
- Author
-
Riccardo Carotenuto
- Subjects
Set (abstract data type) ,Theoretical computer science ,Control and Systems Engineering ,Computer science ,Signal Processing ,Convergence (routing) ,Iterative approximation ,Electrical and Electronic Engineering ,Representation (mathematics) - Abstract
An iterative technique is proposed to efficiently represent n-dimensional discrete mappings from experimental sampled data. The original sampled mapping is approximated, under some assumptions, with a proper set of one-dimensional arrays. The proposed technique highly reduces the severe memory requirements of classical memory-based techniques. A convergence discussion on the proposed algorithm and application examples are presented. Copyright © 2003 John Wiley & Sons, Ltd.
- Published
- 2003
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