Associative Memory using Attribute-Specific Neuron Groups-1: Learning between Multiple Cue Balls

• URL: http://arxiv.org/abs/2512.02319v2
• Date: Fri, 05 Dec 2025 02:16:09 GMT
• Title: Associative Memory using Attribute-Specific Neuron Groups-1: Learning between Multiple Cue Balls
• Authors: Hiroshi Inazawa,
• Abstract summary: The proposed model is based on a previous study on memory and recall of multiple images using the Cue Ball and Recall Net.<n>The system consists of three components, which are C.CB-RN for processing color, S.CB-RN for processing shape, and V.CB-RN for processing size.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: In this paper, we present a new neural network model based on attribute-specific representations (e.g., color, shape, size), a classic example of associative memory. The proposed model is based on a previous study on memory and recall of multiple images using the Cue Ball and Recall Net (referred to as the CB-RN system, or simply CB-RN) [1]. The system consists of three components, which are C.CB-RN for processing color, S.CB-RN for processing shape, and V.CB-RN for processing size. When an attribute data pattern is presented to the CB-RN system, the corresponding attribute pattern of the cue neurons within the Cue Balls is associatively recalled in the Recall Net. Each image pattern presented to these CB-RN systems is represented using a two-dimensional code, specifically a QR code [2].

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