Evolving neural networks with iterative learning scheme for associative memory

Associative Memory Implementation with Artificial Neural Networks

The first description of ANN integrated circuit implements a continuous time analog circuit for AM. The design used a 22 x 22 matrix with 20,000 transistors, averaging 40 transistors per node to implement a Hopfield AM network. The design faced a scalability challenge at higher levels of integration. The paper advocates handling larger problems by a collection of smaller networks or hierarchica...

Cooperative Co-Evolving Neural Networks for Robosoccer Simulation

Recursive neural networks for associative memory

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Associative Memory in Damaged Neural Networks

The content-addressability of random patterns stored in neural networks trained with iterative learning rules is studied numerically under the eeects of synaptic damage. The model of damage is random dilution of couplings with some probability after learning. A simple model based on the distribution of stabilities () is proposed, which allows for the calculation of the storage and retrieval pro...

CHAPTER III Neural Networks as Associative Memory

Associative memories can be implemented either by using feedforward or recurrent neural networks. Such associative neural networks are used to associate one set of vectors with another set of vectors, say input and output patterns. The aim of an associative memory is, to produce the associated output pattern whenever one of the input pattern is applied to the neural network. The input pattern m...