Part 3: brain science, information science and associative memory model

Authors:
Masato Okada
Affiliations:
The University of Tokyo, Kashiwa Chiba, Japan and RIKEN Brain Science Institute, Wako Saitama, Japan
Venue:
New Generation Computing
Year:
2006

Citing 6
Cited 0

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A hierarchy of macrodynamical equations for associative memory

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Multiuser Detection

Multiuser Detection
A statistical-mechanics approach to large-system analysis of CDMA multiuser detectors

IEEE Transactions on Information Theory
Approximate belief propagation, density evolution, and statistical neurodynamics for CDMA multiuser detection

IEEE Transactions on Information Theory

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Abstract

I review recent progress on the associative memory model, which is a kind of neural network model. First, I introduce this model and a mathematical theory called statistical neurodynamics describing its properties. Next, I discuss an associative memory model with hierarchically correlated memory patterns. Initially, in this model, the state approaches a mixed state that is a superposition of memory patterns. After that, it diverges from the mixed state, and finally converges to a memory pattern. I show that this retrieval dynamics can qualitatively replicate the temporal dynamics of face-responsive neurons in the inferior temporal cortex, which is considered to be the final stage of visual perception in the brain. Finally, I show an unexpected link between associative memory and mobile phones (CDMA). The mathematical structure of the CDMA multi-user detection problem resembles that of the associative memory model. It enables us to apply a theoretical framework of the associative memory model to CDMA.