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In this paper, the vision-based hand movement recognition problem is formulated for the universe of discourse of the Brazilian Sign Language. In order to analyze this specific domain we have used the artificial neural networks models based on distance, including neural-fuzzy models. The experiments explored here show the usefulness of these models to extract helpful knowledge about the classes of...
In this paper, an analog current mode implementation of a neuron circuit capable of performing real Gaussian neighborhood taper learning is presented. The neuron cell is compacted with a reusable multiplier that can function as squarer and multiplier for Euclidean and topological distances calculation as well as for Gaussian function characteristics with adjustable learning rate. A four-neuron self-organizing...
This paper presents an on-line, continuously learning mechanism for sequence data. The proposed approach is based on SOINN-DTW method (Okada and Hasegawa, 2007), which is designed for learning of sequence data. It is based on self-organizing incremental neural network (SOINN) and dynamic time warping (DTW). Using SOINNpsilas function represents the topological structure of online input data, the output...
In this paper we propose a method to implement SOM neural network in FPGA circuits: a self organized map neural network with on-chip learning algorithm. The method implies the building of a neural network by generic blocks designed in Mathworks' Simulink environment. The main characteristics of this solution are onchip learning algorithm implementation and high reconfiguration capability and operation...
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