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We propose an associative model for the classification of real-valued patterns. It is an extension of well-known associative model proposed by K. Steinbuch in 1961, which is known to be only useful in the binary case. The proposed extension is tested in several scenarios with images of realistic objects.
In this note we show how a binary memory can be used to recall gray-level patterns. We take as example the α β associative memories recently proposed in Yáñez, Associative Memories based on order Relations and Binary Operators(In Spanish), PhD Thesis, Center for computing Research, February of 2002, only useful in the binary case. Basically, the idea(More)
Pattern reconstruction or pattern restoration in the presence of noise is a main problem in pattern recognition. An essential feature of the noise acting on a pattern is its local nature. If a pattern is split into enough sub-patterns, a few of them will be less or more affected by noise, others will remain intact. In this paper, we propose a simple but(More)
Resumen— En este trabajo se presenta un método basado en la operación de las llamadas redes neuronales dinámicas (RND), para la recomendación musical optimizada. Las redes son entrenadas con las señales de cada melodía, y no con descriptores tradicionales. La propuesta fue probada con una base de datos compuesta por 1,000 melodías, a diferentes frecuencias(More)