A Hybrid Neural Network of Addressable and Content-Addressable Memory

Neural-net inference and content addressable memory

We consider Whittle's probabilistic content addressable memory, the antiphon, which is designed for recovering stored patterns from nonlinear distortions of the input messages. We give an application to content-based image retrieval systems and propose canonical ways of choosing similarity thresholds ensuring statistical consistency.

Survey on Content Addressable Memory and Sparse Clustered Network

Most memory devices store and retrieve data by addressing specific memory locations. As a result, this path often becomes the limiting factor for systems that rely on fast memory accesses. The time required to find an item stored in memory can be reduced considerably if the item can be identified for access by its content rather than by its address. A memory that is accessed in this way is call...

A High-Storage Capacity Content-Addressable Memory and Its Learning Algorithm

Abstrud -Hopfield’s neural networks show retrieval and speed capabilities that make them good candidates for content-addressable memories (CAM’s) in problems such as pattern recognition and optimization. This paper presents a new implementation of a VLSI fully interconnected neural network with only two binary memory points per synapse (the connection weights are restricted to three different v...

Hybrid Network Learning

This paper proposes Neural Network architecture for implementing associative memory. A new model has been developed that has good learning structure and high storage capacity. Hybrid Network Learning comprises interactive counter propagation network and associative memory. Interactive counter propagation network is used for pattern completion. The associative memory is applied for pattern assoc...

Supervised learning and associative memory by the random neural network