Abstract
Memory plays a major role in Artificial Neural Networks. Without memory, Neural Network can not be learned itself. One of the primary concepts of memory in neural networks is Associative neural memories. A survey has been made on associative neural memories such as Simple associative memories (SAM), Dynamic associative memories (DAM), Bidirectional Associative memories (BAM), Hopfield memories, Context Sensitive Auto-associative memories (CSAM) and so on. These memories can be applied in various fields to get the effective outcomes. We present a study on these associative memories in artificial neural networks.
Highlights
Learning is the way we acquire knowledge about the world around us, and it is through this process of knowledge acquisition, that the environment alerts our behavioral responses
Aristotle stated about memory: first, the elementary unit of memory is a sense image and second, association and links between elementary memories serve as the basis for higher level cognition
We presented a Hopfield model with six units, where each node is connected to every other node in the network is given below
Summary
Sagar Yeruva Department of Computer Applications, St. Peter’s Engineering College, Hyderabad. Abstract— Memory plays a major role in Artificial Neural Networks. Neural Network can not be learned itself. One of the primary concepts of memory in neural networks is Associative neural memories. A survey has been made on associative neural memories such as Simple associative memories (SAM), Dynamic associative memories (DAM), Bidirectional Associative memories (BAM), Hopfield memories, Context Sensitive Auto-associative memories (CSAM) and so on. These memories can be applied in various fields to get the effective outcomes. We present a study on these associative memories in artificial neural networks
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