Speech recognition by machines and humans
Speech Communication
Spikes: exploring the neural code
Spikes: exploring the neural code
Coding time-varying signals using sparse, shift-invariant representations
Proceedings of the 1998 conference on Advances in neural information processing systems II
Spiking Neuron Models: An Introduction
Spiking Neuron Models: An Introduction
Robust sound onset detection using leaky integrate-and-fire neurons with depressing synapses
IEEE Transactions on Neural Networks
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The focus of this paper is to propose an explanation for how biological auditory mechanism is able to use spiking neurons to code high bandwidth information using information channels with very slow sampling rates ( 20 Hz). The general approach described in this paper is to decompose the signal into narrow band channels, each of which can be sampled at a frequency that is much lower than the center frequency of the corresponding narrow band filter. The new idea here is that the system can use non-uniform sampling to capture both the amplitude of the modulation and the phase of the carrier signal. In this paper, we first describe a system based on FFT analysis combined with overlapadd and a sampling process where magnitude is digitized but phase is represented using a temporal code of spiking neurons. The coding/decoding mechanism is based on the properties of the refractory period. We demonstrate that it is possible to reduce the bit rate to 50% by coding the carrier phase using the timing of the pulses. In the second part of this paper we show how a biological system may approximate the broadband auditory signal using spiking neurons in conjunction with a simple model of neural refractory period.