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Self-organizing Digital Spike Interval Maps
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由 T Ogawa 著作2011被引用 2 次 — This paper studies digital spike interval maps and its learning algorithm. The map can output a variety of digital spike-trains. In order to learn a desired ...
Self-organizing Digital Spike Interval Maps
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This paper studies digital spike interval maps and its learning algorithm, which can output a variety of digital spike-trains and evolve with ...
Digital spike maps and learning of spike signals
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Basic Learning Characteristics of Digital Spike Maps · Self-organizing Digital Spike Interval Maps · Analysis of digital spike maps based on bifurcating neurons.
Self-Organizing Maps: | Guide books | ACM Digital Library
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Ogawa T and Saito T Self-organizing digital spike interval maps Proceedings of the 18th international conference on Neural Information Processing - Volume ...
Analysis of digital spike maps based on bifurcating neurons
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由 N Horimoto 著作2012被引用 20 次 — Abstract: This paper studies digital spike maps that can generate various periodic spike-trains. In order to analyze the dynamics, we consider two measures ...
Self-organizing maps with dynamic learning for signal ...
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由 J Cho 著作2007被引用 15 次 — The simulation results show that the proposed strategy outperforms conventional vector quantization methods for spike reconstruction. Introduction. Brain– ...
Basic Analysis of Digital Spike Maps
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This paper studies digital spike maps that can generate various periodic spike-trains. In order to analyze the maps, we present a simple analysis algorithm ...
Basic analysis of digital spike maps | Proceedings of the 22nd ...
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This paper studies digital spike maps that can generate various periodic spike-trains. In order to analyze the maps, we present a simple analysis algorithm ...
Digital Dynamical Systems of Spike-Trains
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由 N Horimoto 著作2013被引用 2 次 — This paper studies a simple digital dynamical system that can generate various spike-trains. In order to consider the steady and transient states, ...
Compression of Spike Data Using the Self-Organizing Map
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Motivated by current attempts to use wireless in brain-machine interfaces (BMIs), this paper presents a method for the compression of spike data.