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

• المؤلفون الرئيسيون: Jeyasothy, Abeegithan, Sundaram, Suresh, Sundararajan, Narasimhan
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2020
• الموضوعات: Engineering::Computer science and engineering; Gamma-aminobutyric Acid (GABA)-switch
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/144620

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...