Aug 8, 2005 · SUMMARY. Information transmission among biological neurons is carried out by a complex series of spike signals. The input inter-spike ar-.
In this paper, a new scheme which utilizes the input inter-spike intervals (ISI) for decoding an input spike train is proposed. A spike train consists of a ...
A new scheme which utilizes the input inter-spike intervals (ISI) for decoding an input spike train is proposed and can be used for neurons which have ...
Aug 1, 2005 · In this paper, a new scheme which utilizes the input inter-spike intervals (ISI) for decoding an input spike train is proposed.
Sep 25, 2022 · Spiking neural networks (SNNs) using time-to-first-spike (TTFS) codes, in which neurons fire at most once, are appealing for rapid and low power ...
Aug 1, 2005 · This decoding scheme can also be used for neurons which have multiple synaptic inputs but for which each synapse receives a single spike within ...
Spiking Neural Network Inter-Spike Time Based Decoding Scheme. Authors. Hesham H. AMIN; Robert H. FUJII. Downloads. Requires Subscription PDF. Published. 2005- ...
Here we propose an ANN to SNN conversion methodology that uses a time-based coding scheme, named At-most-two-spike Exponential Coding (AEC), and a corresponding ...
Jan 28, 2021 · This paper proposes a novel Brain-Inspired Spiking Neural Network (BI-SNN) model for incremental learning of spike sequences.
May 25, 2024 · The decoding process involves analyzing the spiking activity of the neurons in the network to extract useful information. This process involves ...
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