Ponencia
Building Blocks for Spikes Signals Processing
Autor/es | Jiménez Fernández, Ángel Francisco
![]() ![]() ![]() ![]() ![]() ![]() ![]() Linares Barranco, Alejandro ![]() ![]() ![]() ![]() ![]() ![]() ![]() Paz Vicente, Rafael ![]() ![]() ![]() ![]() ![]() ![]() ![]() Jiménez Moreno, Gabriel ![]() ![]() ![]() ![]() ![]() ![]() ![]() Civit Balcells, Antón ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Departamento | Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores |
Fecha de publicación | 2010 |
Fecha de depósito | 2019-12-16 |
Publicado en |
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ISBN/ISSN | 978-1-4244-6916-1 2161-4393 |
Resumen | Neuromorphic engineers study models and
implementations of systems that mimic neurons behavior in the
brain. Neuro-inspired systems commonly use spikes to
represent information. This representation has several
advantages: ... Neuromorphic engineers study models and implementations of systems that mimic neurons behavior in the brain. Neuro-inspired systems commonly use spikes to represent information. This representation has several advantages: its robustness to noise thanks to repetition, its continuous and analog information representation using digital pulses, its capacity of pre-processing during transmission time, ... , Furthermore, spikes is an efficient way, found by nature, to codify, transmit and process information. In this paper we propose, design, and analyze neuro-inspired building blocks that can perform spike-based analog filters used in signal processing. We present a VHDL implementation for FPGA. Presented building blocks take advantages of the spike rate coded representation to perform a massively parallel processing without complex hardware units, like floating point arithmetic units, or a large memory. Those low requirements of hardware allow the integration of a high number of blocks inside a FPGA, allowing to process fully in parallel several spikes coded signals. |
Identificador del proyecto | P06-TIC-O1417
![]() TEC2009-10639-C04-02 ![]() TEC2006-11730-C03-02 ![]() |
Cita | Jiménez Fernández, Á.F., Linares Barranco, A., Paz Vicente, R., Jiménez Moreno, G. y Civit Balcells, A. (2010). Building Blocks for Spikes Signals Processing. En IJCNN 2010 : International Joint Conference on Neural Networks Barcelona, España: IEEE Computer Society. |
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