A general-purpose dynamically reconfigurable SVM

This paper presents an hardware implementation of the Sequential Minimal Optimization (SMO) for the Support Vector Machine (SVM) training phase. A general-purpose reconfigurable architecture, aimed to partial reconfiguration FPGAs, is developed, i.e., it supports different sizes of training sets, wi...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Gomes Filho, Jonas, Raffo, Mario, Strum, Marius, Wang Jiang Chau
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Data analysis Field programmable gate arrays Frequency Hardware Iterative algorithms Quadratic programming Reconfigurable architectures Support vector machine classification Support vector machines Testing
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