SEFRON : a new spiking neuron model with time-varying synaptic efficacy function for pattern classification

• Main Authors: Jeyasothy, Abeegithan, Sundaram, Suresh, Sundararajan, Narasimhan
• 其他作者: School of Computer Science and Engineering
• 格式: Article
• 語言: English
• 出版: 2020
• 主題: Engineering::Computer science and engineering; Gamma-aminobutyric Acid (GABA)-switch
• 在線閱讀: https://hdl.handle.net/10356/144620
• 機構: Nanyang Technological University

This paper presents a new time-varying long-term Synaptic Efficacy Function-based leaky-integrate-and-fire neuRON model, referred to as SEFRON and its supervised learning rule for pattern classification problems. The time-varying synaptic efficacy function is represented by a sum of amplitude modula...