Adding temporal plasticity to a self-organizing incremental neural network using temporal activity diffusion
Vector Quantization (VQ) is a classic optimization problem and a simple approach to pattern recognition. Applications include lossy data compression, clustering and speech and speaker recognition. Although VQ has largely been replaced by time-aware techniques like Hidden Markov Models (HMMs) and Dyn...
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Format: | Others |
Language: | English |
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KTH, Skolan för datavetenskap och kommunikation (CSC)
2015
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Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-180346 |