Tridimensional Pattern Reconstruction by Using Weightless Artificial Neural Networks
نویسنده
چکیده
1. ABSTRACT This paper describes the structure and behavior of a system, composed by a set of weightless artificial neural networks, which is capable of learning different images and then reconstructing an image according to the closest learned pattern. This paper presents a technique which considers Hamming distance for pattern learning and reconstruction, therefore it is posible to study the mechanism for representing information inside weightless artificial neural networks.
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