DIGITAL ARCHITECTURES FOR ADAPTIVE PROCESSING OF MEASUREMENT DATA |
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| Andrea Boni, Dario Petri, Ivan Biasi |
- Abstract:
- In this paper we describe the design of digital architectures suitable for the implementation of measurement data classification based on Support Vector Machines (SVMs). The performance of such architectures are then analyzed. The proposed approach can be applied for solving identification and inverse modelling problems, and for processing complex measurement data. Two very different case studies where real-time processing is of paramount importance are discussed: a nonlinear channel equalization and a high energy physics classification task.
- Download:
- IMEKO-TC4-2004-035.pdf
- DOI:
- -
- Event details
- IMEKO TC:
- TC4
- Event name:
- TC4 Symposium 2004
- Title:
- XIII IMEKO TC4 International Symposium on Measurements for Research and Industrial Applications (together with IXth International Workshop on ADC Modeling and Testing, IWADC)
- Place:
- Athens, GREECE
- Time:
- 29 September 2004 - 01 October 2004