A Closed Form Solution for Multiple-Input Spike Based Adaptive Filters

Abstract — Neurons are point process systems, in the sense that the inputs and output which are spike trains can be treated as point processes. System identification of a point process system has been studied mostly with single input. However, multiple input is required in many applications such as liquid state machines or neural prosthetics. We propose a simple multiple-input spike based adaptive filter which is based on an integrate-and-fire neuron model. The optimal closed solution is derived, and the performance is analyzed with respect to noise in various parameters and measurement. I