Spike-based analog-digital neuromorphic information processing system for sensor applications
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessRestricted access - publisher's policy
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.
CitationSanchez , 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.
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