liquid state mechanics, pattern recognition
The applicability of complex networks of spiking neurons as a general purpose machine learning technique remains open. Building on previous work using macroscopic exploration of the parameter space of an (artificial) neural microcircuit, we investigate the possibility of using a liquid state machine to solve two real-world problems: stockpile surveillance signal alignment and spoken phoneme recognition.
Original Publication Citation
Eric Goodman and Dan Ventura, "Spatiotemporal Pattern Recognition via Liquid State Machines", Proceedings of the International Joint Conference on Neural Networks, pp. 7579-7584, July 26.
BYU ScholarsArchive Citation
Goodman, Eric and Ventura, Dan A., "Spatiotemporal Pattern Recognition via Liquid State Machines" (2006). Faculty Publications. 306.
Physical and Mathematical Sciences
© 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Copyright Use Information