Spike-based analog-digital neuromorphic information processing system for sensor applications
Tipo de documentoTexto en actas de congreso
Fecha de publicación2013
EditorInstitute of Electrical and Electronics Engineers (IEEE)
Condiciones de accesoAcceso restringido por política de la editorial
A spiking-neuron-based system that combines analog and digital multi-processor implementations for the bio-inspired processing of sensors is reported. This combination allows creating a powerful bio-inspired multiple-input sensor processing system for environment perception applications. The analog front-end encodes the input signal in a signed spike representation, which is further processed by means of a digital Spiking Neural Network (SNN) on a Single-Instruction Multiple-Data (SIMD) multiprocessor. The spike distribution for both systems is based on Address-Event Representation (AER) scheme, asynchronous for the Analog Pre-Processor (APP) and synchronous for the Digital Multi-Processor (DMP), synchronized by means of an AER transceiver. A proof-of-concept application of the system being able to process sensory information has been demonstrated. The system utilizes 30-neurons emulated by the DMP to process spike-encoded information provided by its analog counterpart, enabling the feature extraction of the input signal. The frequency detection capability of the system is experimentally reported.
CitaciónSanchez , G. [et al.]. Spike-based analog-digital neuromorphic information processing system for sensor applications. A: IEEE International Symposium on Circuits and Systems. "2013 IEEE International Symposium on Circuits and Systems (ISCAS 2013) : Beijing, China, 19 - 23 May 2013". Beijing-Pekín: Institute of Electrical and Electronics Engineers (IEEE), 2013, p. 1624-1627.
Versión del editorhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6572173&tag=1
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