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Signal Quantization using a Leaky Integrate-and-Fire neuron

Abstract : – In this paper we present a quantizer based on the Leaky-Integrate and Fire (LIF) neural model. The LIF is the model according to which function the ganglion cells. Ganglion cells are placed in the layer of the retina responsible for the encoding of visual information, before it is transmitted to the brain through the optic nerve. In general, the LIF quantizes intensity values according to a threshold value, a given observation time, the presence or not of a refractory period in the neuron and the parameters R and C characterizing the resistance and capacity of the neural model. Varying the value of the threshold and observation time we tested experimentally the behaviour of the LIF quantizer to a given input signal and through this work we present the results and the comparison to the uniform scalar quantizer and the Lloyd quantizer.
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https://hal.archives-ouvertes.fr/hal-01650750
Contributor : Melpomeni Dimopoulou <>
Submitted on : Tuesday, November 28, 2017 - 2:37:25 PM
Last modification on : Tuesday, May 26, 2020 - 6:50:35 PM

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Melpomeni Dimopoulou, Marc Antonini. Signal Quantization using a Leaky Integrate-and-Fire neuron. GRETSI 2017, Sep 2017, Juan-Les-Pins, France. ⟨hal-01650750⟩

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