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Chapter 6 Associative Models

Chapter 6 Associative Models. Introduction. Associating patterns which are similar, contrary, in close proximity (spatial), in close succession (temporal) or in other relations Associative recall/retrieve evoke associated patterns recall a pattern by part of it: pattern completion

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Self Organization: Hebbian Learning

Self Organization: Hebbian Learning. CS/CMPE 537 – Neural Networks. Introduction. So far, we have studied neural networks that learn from their environment in a supervised manner Neural networks can also learn in an unsupervised manner as well. This is also known as self organized learning

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Unsupervised Learning

Unsupervised Learning. Motivation: Given a set of training examples with no teacher or critic, why do we learn? Feature extraction Data compression Signal detection and recovery Self organization Clustering Information can be found about data from inputs. Principal Component Analysis.

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