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In this paper, we propose a successive learning method in hetero-associative memories, such as Bidirectional Associative Memories and Multidirectional Associative Memories, using chaotic neural networks. It can distinguish unknown data from the stored known data and can learn the unknown data successively. The proposed model makes use of the difference in(More)
In this paper, we propose a Chaotic Complex-valued Bidirectional Associative Memory (CCBAM) which can realize one-to-many associations of multi-valued patterns. The proposed model is based on the Bidirectional Associative Memory, and is composed of complex-valued neurons and chaotic complex-valued neurons. In the proposed model, associations of multi-valued(More)
In this paper, we propose a Kohonen feature map associative memory with area representation for sequential patterns. This model is based on the Kohonen feature map associative memory with area representation and the Kohonen feature map associative memory for temporal sequences. The proposed model can learn sequential patterns successively, and has(More)
Abstract—In this paper, we propose a chaotic complexvalued associative memory which can realize a dynamic association of multi-valued patterns. The proposed model is based on a complex-valued associative memory and a chaotic associative memory. The complex-valued associative memory can treat multi-valued patterns, and the chaotic associative memory can(More)
In this paper, we propose an office layout support system using genetic algorithm which can generate layout plans for polygonal space. The proposed system has two phases; (1) generation of room arrangement plans and (2) generation of layout plans for workspace. In the proposed system, some conditions on rooms and furniture are given by a user, some room(More)
In this paper, we propose a Hetero Chaotic Associative Memory for Successive Learning (HCAMSL) with give up function. The proposed model is based on a Chaotic Associative Memory for Successive Memory (CAMSL). In the proposed HCAMSL, the learning process and the recall process are not divided. When an unstored pattern is given to the network, the HCAMSL can(More)
In this paper, we propose a hetero chaotic associative memory for successive learning with multi-winners competition (HCAMSL-MW). The proposed model is based on a hetero chaotic associative memory for successive learning (HCAMSL) and the multi winners self-organizing neural network (MWSONN). In most of the conventional neural network models, the learning(More)
In this research, we proposed a similarity-based image retrieval by self-organizing map with refractoriness. In the self-organizing map with refractoriness, the plural neurons in the map layer corresponding to the input can fire sequentially because of the refractoriness. The image retrieval system using the self-organizing map with refractoriness makes use(More)