Brain inspired automatic directory

Itay Azaria, Shlomi Dolev, Ariel Hanemann, Rami Puzis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The fascinating question of the relation of information and coding theory to the memories stored in the brain is our research scope. We speculate there is a similar code used to represent different memories, rather than unique code for different memories. The uniform cortex structure supports our speculation. Recently we suggested holographic coding that can fit Pribram's holographic memory theory. Using the holographic coding metaphor, the memory should be retrieved by a reference beam as in a hologram. We explore the possibility that the brain learns its directory (possibly in the temporal lobe), during memory consolidation. This directory is a neural network that is used for sending signals to the cortex to recall memories. The network learns to distinguish between objects during saving, in order to signal the correct recall. Haar features (HF) are 0/1 matrices used for face recognition. We use HF to learn to differentiate between objects. Namely when objects are saved, our system learns what is the best set of HF to distinguish between them using a genetic algorithm. The sets of HF are tested for the best clustering set without knowing their semantics (unsupervised learning). Later semantics is learned by interaction with the environment. The best sets continue to the next generation. We chose unsupervised learning due to the idea that it is possible to distinguish objects without knowing their identity.

Original languageEnglish
Title of host publicationProceedings - 2nd International Symposium on Stochastic Models in Reliability Engineering, Life Science, and Operations Management, SMRLO 2016
EditorsAnatoly Lisnianski, Ilia Frenkel
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages197-201
Number of pages5
ISBN (Electronic)9781467399418
DOIs
StatePublished - 11 Mar 2016
Event2nd International Symposium on Stochastic Models in Reliability Engineering, Life Science, and Operations Management, SMRLO 2016 - Beer Sheva, Israel
Duration: 15 Feb 201618 Feb 2016

Publication series

NameProceedings - 2nd International Symposium on Stochastic Models in Reliability Engineering, Life Science, and Operations Management, SMRLO 2016

Conference

Conference2nd International Symposium on Stochastic Models in Reliability Engineering, Life Science, and Operations Management, SMRLO 2016
Country/TerritoryIsrael
CityBeer Sheva
Period15/02/1618/02/16

Keywords

  • Haar features
  • Semantic memory
  • Unsupervised learning

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Modeling and Simulation
  • Statistics and Probability
  • Agricultural and Biological Sciences (miscellaneous)
  • Strategy and Management

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