An Online EHW Pattern Recognition System Applied to Sonar Spectrum Classification

  • Kyrre Glette
  • Jim Torresen
  • Moritoshi Yasunaga
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4684)


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 0.5μs.


Functional Unit Hardware Implementation Evolvable Hardware Incremental Evolution High Level Module 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Kyrre Glette
    • 1
  • Jim Torresen
    • 1
  • Moritoshi Yasunaga
    • 2
  1. 1.University of Oslo, Department of Informatics, P.O. Box 1080 Blindern, 0316 OsloNorway
  2. 2.University of Tsukuba, Graduate School of Systems and Information Engineering, 1-1-1 Ten-ou-dai, Tsukuba, IbarakiJapan

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