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Published in:
2007 | OriginalPaper | Chapter
An Online EHW Pattern Recognition System Applied to Sonar Spectrum Classification
Authors : Kyrre Glette, Jim Torresen, Moritoshi Yasunaga
Published in: Evolvable Systems: From Biology to Hardware
Publisher: Springer Berlin Heidelberg
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An evolvable hardware (EHW) system for high-speed sonar return classification has been proposed. The system demonstrates an average accuracy of 91.4% on a sonar spectrum data set. This is better than a feed-forward neural network and previously proposed EHW architectures. Furthermore, this system is designed for online evolution. Incremental evolution, data buses and high level modules have been utilized in order to make the evolution of the 480 bit-input classifier feasible. The classification has been implemented for a Xilinx XC2VP30 FPGA with a resource utilization of 81% and a classification time of 0.5
μ
s.