A generalized analog implementation of piecewise linear neuron models using CCII building blocks

作者：Soleimani Hamid; Ahmadi Arash^*; Bavandpour Mohammad; Sharifipoor Ozra

来源：Neural Networks, 2014, 51: 26-38.

DOI：10.1016/j.neunet.2013.12.004

• Spiking neural network
• Piecewise linear model
• CCII
• Programmable analog circuit
• Bifurcation

This paper presents a set of reconfigurable analog implementations of piecewise linear spiking neuron models using second generation current conveyor (CCII) building blocks. With the same topology and circuit elements, without W/L modification which is impossible after circuit fabrication, these circuits can produce different behaviors, similar to the biological neurons, both for a single neuron as well as a network of neurons just by tuning reference current and voltage sources. The models are investigated, in terms of analog implementation feasibility and costs, targeting large scale hardware implementations. Results show that, in order to gain the best performance, area and accuracy; these models can be compromised. Simulation results are presented for different neuron behaviors with CMOS 350 nm technology.

• 出版日期2014-3