Roseli A. Francelin Romero

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Blind Signal and Image Processing (BSIP) is an exciting and emerging research topic in fields such as neural networks, advanced statistics, data mining, and biomedical signal/image processing and, over the past decade, has established solid theoretical foundations and many real-world applications. The “blind” processing of signals, based on unsupervised(More)
Attention is a critical mechanism for visual scene analysis. By means of attention, it is possible to break down the analysis of a complex scene to the analysis of its parts through a selection process. Empirical studies demonstrate that attentional selection is conducted on visual objects as a whole. We present a neurocomputational model of object-based(More)
In this work, an Elman recurrent neural network is used for automatic musical structure composition based on the style of a music previously learned during the training phase. Furthermore, a small fragment of a chaotic melody is added to the input layer of the neural network as an inspiration source to attain a greater variability of melodies. The neural(More)
Social robots are embodied agents that are part of a heterogeneous group: a society of robots or humans. They are able to recognize human beings and each other, and engage in social interactions. They possess histories and they explicitly communicate and learn from interactions. The construction of social robots may strongly benefit from using a robotic(More)
This paper describes the design and implementation of a learning method in the context of robotic architecture for the social interactive simulation. This method is based on TG algorithm, named ETG, but use incremental process during the episode of learning. So, it does not use secondary memory to storage examples before insert in relational regression(More)