Koeppl, H. (2006)
An Adaptive Cellular Network for Subspace Extraction.
2006 Fortieth Asilomar Conference on Signals, Systems and Computers.
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
The work proposes a novel network structure for the least mean square error reconstruction (LMSER) principle to perform principal subspace analysis (PSA). The LMSER principle allows for an efficient parallel and robust implementation of PSA, where each individual processing cell contains a local adaptation algorithm. Instead of the classical feedforward network topology this work introduces a recursive topology. It is also shown that the fully connected two-layered network can be represented by a network of multiple locally connected processing layers. This locally coupled network closely resembles cellular nonlinear networks (CNN) and is very suitable for a VLSI (very-large-scale-integration) implementation.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2006 |
| Autor(en): | Koeppl, H. |
| Art des Eintrags: | Bibliographie |
| Titel: | An Adaptive Cellular Network for Subspace Extraction |
| Sprache: | Englisch |
| Publikationsjahr: | 2006 |
| Ort: | Pacific Grove, CA, USA |
| Verlag: | IEEE |
| Veranstaltungstitel: | 2006 Fortieth Asilomar Conference on Signals, Systems and Computers |
| URL / URN: | http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=417672... |
| Kurzbeschreibung (Abstract): | The work proposes a novel network structure for the least mean square error reconstruction (LMSER) principle to perform principal subspace analysis (PSA). The LMSER principle allows for an efficient parallel and robust implementation of PSA, where each individual processing cell contains a local adaptation algorithm. Instead of the classical feedforward network topology this work introduces a recursive topology. It is also shown that the fully connected two-layered network can be represented by a network of multiple locally connected processing layers. This locally coupled network closely resembles cellular nonlinear networks (CNN) and is very suitable for a VLSI (very-large-scale-integration) implementation. |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Bioinspirierte Kommunikationssysteme 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik |
| Hinterlegungsdatum: | 04 Apr 2014 12:31 |
| Letzte Änderung: | 23 Sep 2021 14:32 |
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