In this work a novel analysis methodology of SVMs optimal solutions is presented. Such a methodology is based on a multiobjective optimization algorithm which exploits a genetic search paradigm. The application field is the design of smart micro-sensors, where both classification performance and complexity criteria have to be considered in order to balance accuracy and power consumption requirements.
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Titolo: | Model selection for power efficient analysis of measurement data |
Autori: | |
Data di pubblicazione: | 2006 |
Abstract: | In this work a novel analysis methodology of SVMs optimal solutions is presented. Such a methodology is based on a multiobjective optimization algorithm which exploits a genetic search paradigm. The application field is the design of smart micro-sensors, where both classification performance and complexity criteria have to be considered in order to balance accuracy and power consumption requirements. |
Handle: | http://hdl.handle.net/11582/60799 |
ISBN: | 9780780393608 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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