Author:
Viacheslav Antsiperov
Affiliation:
Kotelnikov Institute of Radioengineering and Electronics of RAS, Mokhovaya 11-7, Moscow, 125009, Russia
Keyword(s):
Neuromorphic Computing, Data-Event Streams, Poisson Counts, Sampling Representation, Receptive Fields, Most Powerful Unbiased Test, Center / Surround Inhibition, Perceptual Coding, Marr’s Image Primal Sketch.
Abstract:
The work is devoted to a new approach to neuromorphic encoding of streaming data. An essential starting point of the proposed approach is a special (sampling) representation of input data in the form of a stream of discrete events (counts), modeling the firing events of biological neurons. Considering the specifics of the sampling representation, we have formed a generative model for the primary processing of the count stream. That model was also motivated by known neurophysiological facts about the structure of receptive fields of sensory systems of living organisms that implement universal mechanisms (including central-circumferential inhibition) of biological neural networks, particularly the brain. To list the main ideas and consolidate the notations used, the article provides a brief overview of the features and most essential provisions of the proposed approach. The new results obtained within the framework of the approach, related to the analysis of neuromorphic encoding (with
distortions) of streaming data, are discussed. The issues of possible decoding/restoration of the original data are discussed in the context of what Marr called the primary sketch. The results of computer modelling of the developed encoding/decoding procedures are presented, approximate numerical characteristics of their quality are given.
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