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3D robotic vision is proposed using a neural network model that forms sparse distributed memory traces of spatiotemporal episodes of an object. These episodes are generated by the robot interaction with the environment or by robot's movement around 3D object and its perspective to the objects. The traces are distributed in each cell and synapse that participates in many traces. This sharing of representational...
In order to generate or tune fuzzy rules, Neuro-Fuzzy learning algorithms with Gaussian type membership functions based on gradient-descent method are well known. In this paper, we propose a new learning approach, the Quaternion Neuro-Fuzzy learning algorithm. This method is an extension of the conventional method to four-dimensional space by using a quaternion neural network that maps quaternion...
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