In this paper a new design procedure to design associative memories storing grey-scale images is presented. It is based on a locally connected multilayer Hopfield neural network, with both intra-layer and inter-layer connections. The proposed architecture is an evolution of a previous work based on the decomposition of the image with 2L gray levels into L binary patterns, stored in L uncoupled neural networks: that allows to store images with the commonly used number of 256 gray levels. The approach presented in this paper is based on a suitable decomposition of the grey-scale image into binary images, stored in Hopfield neural networks with bipolar states. The learning algorithm, used to store the binary images, guarantees asymptotic stability of the stored patterns, has a low computational cost, and allows to control the precision of the connection weights. Some design examples are presented to show the effectiveness of the proposed method.

Costantini, G. (2006). Locally connected Hopfield multilayer network for associative memories storing 256 levels grey-scale images, 5(7), 961-968.

Locally connected Hopfield multilayer network for associative memories storing 256 levels grey-scale images

COSTANTINI, GIOVANNI
2006-01-01

Abstract

In this paper a new design procedure to design associative memories storing grey-scale images is presented. It is based on a locally connected multilayer Hopfield neural network, with both intra-layer and inter-layer connections. The proposed architecture is an evolution of a previous work based on the decomposition of the image with 2L gray levels into L binary patterns, stored in L uncoupled neural networks: that allows to store images with the commonly used number of 256 gray levels. The approach presented in this paper is based on a suitable decomposition of the grey-scale image into binary images, stored in Hopfield neural networks with bipolar states. The learning algorithm, used to store the binary images, guarantees asymptotic stability of the stored patterns, has a low computational cost, and allows to control the precision of the connection weights. Some design examples are presented to show the effectiveness of the proposed method.
2006
Pubblicato
Rilevanza internazionale
Articolo
Sì, ma tipo non specificato
Settore ING-IND/31 - ELETTROTECNICA
English
Associative memories; Finite precision weights; Grey-scale images; Hopfield neural networks
Costantini, G. (2006). Locally connected Hopfield multilayer network for associative memories storing 256 levels grey-scale images, 5(7), 961-968.
Costantini, G
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/52623
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