Team:USP-UNESP-Brazil/Associative Memory/Background

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(Hopfield Associative Memory Networks)
(Hopfield Associative Memory Networks)
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Figure 1 shows the selection process of weights of connections between adjacent cells. To add more patterns, we have to sum the network of weights of the new pattern to the old network. (as shown in Figure 2)
Figure 1 shows the selection process of weights of connections between adjacent cells. To add more patterns, we have to sum the network of weights of the new pattern to the old network. (as shown in Figure 2)
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[[File:009.JPG|center|400px|caption|]]
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[[File:009.JPG|center|500px|caption|]]
The Hopfield model for the construction of an associative memory network using bacteria is a good choice because of its simplicity and strength. The same methodology can be used to the construction of networks with other architectures, such as the “perceptrons”. One step forward is the way how to deal with continuous biological variables, because the standard model uses discrete ones.
The Hopfield model for the construction of an associative memory network using bacteria is a good choice because of its simplicity and strength. The same methodology can be used to the construction of networks with other architectures, such as the “perceptrons”. One step forward is the way how to deal with continuous biological variables, because the standard model uses discrete ones.

Revision as of 15:33, 22 September 2012