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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)
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)
In many real situations, randomness is considered to be uncertainty or even confusion which impedes human beings from making a correct decision. Here we study the combined role of randomness and determinism in particle dynamics for complex network community detection. In the proposed model, particles walk in the network and compete with each other in such a(More)
Potential field is a reactive method that has been used for trajectory control of mobile robots. In this method the robot behaves like a particle moving under the influence of an artificial potential produced by the target and the obstacles. This method has lower computational cost than others that utilize maps as a world model. However, one problem or this(More)
An increasing interest in the design of mobile robots has been observed in recent years, which is mainly motivated by technological advances that may allow their application to consumer markets, in addition to industrial areas.Although sophisticated techniques have been developed, choosing the appropriate hardware-software partitioning and programming robot(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 paper, a Visual Selection and a Shifting Mechanisms based on a lattice of coupled chaotic Wilson-Cowan oscillators is proposed. The oscillators representing each object in a given visual scene are synchronized to produce a chaotic trajectory. A cooperation and competition mechanisms are also introduced to accelerate oscillating frequency of the(More)