Associative Memory using Attribute-Specific Neuron Groups-1: Learning between Multiple Cue Balls
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arXiv
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866915655627833344 |
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| author | Inazawa, Hiroshi |
| author_facet | Inazawa, Hiroshi |
| contents | 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]. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_02319 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Associative Memory using Attribute-Specific Neuron Groups-1: Learning between Multiple Cue Balls Inazawa, Hiroshi Neural and Evolutionary Computing D.2; I.5 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]. |
| title | Associative Memory using Attribute-Specific Neuron Groups-1: Learning between Multiple Cue Balls |
| topic | Neural and Evolutionary Computing D.2; I.5 |
| url | https://arxiv.org/abs/2512.02319 |