1-D/2-D/3-D Hopfield Associative Memories

EasyChair Preprint no. 2448

Abstract

In this research paper storage as well as retrieval of
1-D/2-D/3-D information using Hopfield type Associative Memories
(AMs) is discussed. Various Artificial Neural Networks
(ANN) architectures are proposed. Also, implementational issues
associated with those Associative Memories are discussed. Cascade
connection of AM and Convolutional Neural Network is
proposed for noise immunity.
 

Keyphrases: associative memory, Hopfield neural network, stable states, Synaptic weights

@Booklet{EasyChair:2448,
  author = {Rama Garimella and Jyothi Prasanna Gc and Vidya Sree Vankam and Maha Lakshmi Bairaju and Manasa Jagannadhan},
  title = {1-D/2-D/3-D   Hopfield  Associative  Memories},
  howpublished = {EasyChair Preprint no. 2448},

  year = {EasyChair, 2020}}