ARTIFICIAL NEURAL NETWORKS BIDIRECTIONAL ASSOCIATIVE MEMORY

ARTIFICIAL NEURAL NETWORKS BIDIRECTIONAL ASSOCIATIVE MEMORY

ABSTRACT:

This paper focuses on the bidirectional associative memory its features and the future aspects and the current context of application BAM is a type of neural network. Artificial neural network (Ann’s) resembled the human nervous system, with algorithms consisting of weighted interconnecting processing units (like neural map of the human brain). To address a particular problem using Ann’s, the interrelated connections are tuned and the value of weights between units is needed. Neural network is a new unexplored topic of interest for the computer scientists.

Bam comes under recurrent types of network called Hopfield network? BAM is a resonance model, in the sense that information is passed back and forth between two layers of units until a stable sate is reached. The Hopfield network is said to be auto associative, because it uses a partial and noisy pattern to recall the best match of itself.

Applications of BAM include: 1ASSOCIATIVE NEURAL MEMORIES:
Associative neural memories are a class of artificial neural networks (connectionist nets) which have gained substantial attention relative to other neural net paradigms. Associative memories have been the subject of research 2) NOISE TOLERANCY:
This paper analyzes the sensitivity to noise in BAM (Bidirectional Associative Memory), and then proves the noise immunity of BAM relates not only to the minimum absolute value of net inputs (MAV) but also to the variance of weights associated with synapse connections

Case studies about the NEURAL COMPUTATION: - Many scientists and engineers now use neural networks to tackle problems that are either intractable or unrealistically time consuming to solve, through traditional computational strategies. FAULT TOLERANT SYSTEMS. Recent advances in computer technology have made the design of large and very flexible associative processors possible.

The future aspects of BAM such as DATABASE MANAGEMENT SYSTEM and NATURAL LANGUAGE LEARNING THROUGH ABSTRACT MEMORY and LIFE AND ROBOTICs’’’’ are also featured.


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