This paper investigates an information-theoretic design principle, intended to support an evolution of a memory structure fitting a specific selection pressure: associative information transfer through the structure. The proposed criteria measure how much does associativity in memory add to the information transfer in terms of precision, recall and effectiveness. The study also introduces a con...

The paper presents a model for associative memory, based on the idea of a roaming random set. It is very robust, at the expense of quite some redundancy. Thinking, consciousness and various features of memory can be interpreted in terms of the memory model. Like in the von Neumann computer the larger part of operational routines can be stored in the same memory

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We propose a molecular associative memory model, by combining auto-logistic specifications which capture statistical dependencies within the local neighborhood systems of the exposed knowledge, with the bio-inspired DNA-based molecular operations which store and evolve the memory. Our model, characterized by only the local dependencies of the spatial binary data, allows to capture only a fewer ...

This paper presents a generalized associative memory model, which stores a collection of tuples whose components are sets rather than scalars. It is shown that all library patterns are stored stably. On the other hand spurious memories may develop. Applications of this model to storage and retrieval of naturallyarising generalized sequences in bioinformatics are presented. The model is shown to...

A major challenge to understanding cortical function is the complexity found both at the single cell and microcircuit levels. Here we outline what is known about the microcircuitry of the CA1 region of the mammalian hippocampus. We then explore the possible functional roles of the variety of neuronal types within this microcircuit during dynamic information processing. This is considered within...

Hopfield model of associative memory is studied in this work. In particular, two main problems that it possesses: the apparition of spurious patterns in the learning phase, implying the well-known effect of storing the opposite pattern, and the problem of its reduced capacity, meaning that it is not possible to store a great amount of patterns without increasing the error probability in the ret...

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Inspired by the theory of neuronal group selection (TNGS), we have carried out an analysis of the capacity of convergence of a multi-level associative memory based on coupled generalized-brain-state-in-a-box (GBSB) networks through evolutionary computation. The TNGS establishes that a memory process can be described as being organized, functionally, in hierarchical levels where higher levels co...

This paper describes an approach to two-dimensional object recognition. Complex-log conformal mapping is combined with a distributed associative memory l o create a system which recognizes objects regardless of changes in rotation or scale. Recalled information from the memorized database is used to classify an object, reconstruct the memorized version of the object, and estimate the magnitude ...