Efficient non-iterative fixed-period SVM training architecture for FPGAs

Abstract

A method for efficient non-iterative fixed-period SVM training is presented. A highly pipelined, parallel, and concurrent systolic processing-based hardware architecture overview for FPGA implementation is also provided. The architecture's training performance is simulated in software and tested successfully by solving two classification problems utilising… (More)

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