Abstract The growing number of edge devices in everyday life generates a considerable amount data that current AI algorithms, like artificial neural networks, cannot handle inside with limited bandwidth, memory, and energy available. Neuromorphic computing, low-power oscillatory networks (ONNs), is an alternative attractive solution to solve complex problems at the edge. However, ONN currently ...

DOWNLOAD http://bit.ly/1OslRBc Artificial neural networks: theory and applications This comprehensive tutorial on artifical neural networks covers all the important neural network architectures as well as the most recent theory-e.g., pattern recognition, statistical theory, and other mathematical prerequisites. A broad range of applications is provided for each of the architectures. Artificial ...

We study the phenomenon of phase transition occurring in sparse associative neural networks, which is characterized by the abrupt emergence of associative properties with the growth of network connectivity. It is shown that this discontinuous behaviour is caused by the specific way of architecture selection. Based on empirical results the relationship among critical parameters is suggested.

In the field of robotics real-time image processing can provide the information necessary for mobile robots to execute a task in indoor environment. In this paper the application of a simple neural network-based system to translation and scale-invariant object recognition in the artificial vision structure of a mobile robot is proposed. The suggested bio-inspired vision system is mainly constit...

Recently many promising results have been shown on face recognition related problems. However, ageinvariant face recognition and retrieval remains a challenge. Inspired by the observation that age variation is a nonlinear but smooth transform and the ability of auto-encoder network to learn latent representations from inputs, in this paper, we propose a new neural network model called coupled a...

Why anticipatory processes correspond to cognitive abilities of living systems? To be adapted to an environment, behaviors need at least i) internal representations of events occurring in the external environment; and ii) internal anticipations of possible events to occur in the external environment. Interactions of these two opposite but complementary cognitive properties lead to various patte...

1 Abstract The ability of human beings to retrieve information on the basis of associated cues continues to elicit great interest among researchers. Investigations of how the brain is capable to make such associations from partial information have led to a variety of theoretical neural network models that act as associative memories. Several researchers have had signiicant success in retrieving...

Modular architecture is a hallmark of many brain circuits. In the cerebral cortex, in particular, it has been observed that reciprocal connections are often present between functionally interconnected areas that are hierarchically organized. We investigate the effect of reciprocal connections in a network of modules of simulated spiking neurons. The neural activity is recorded by means of virtu...

For decades, computational intelligence techniques have been developed and applied to many real world problems. In this paper, tree architectures of fuzzy neural networks are applied to Auto MPG prediction problem. The dataset concerns city-cycle fuel consumption in miles per gallon, to be predicted in terms of 3 multivalued discrete and 5 continuous attributes. Tree architectures of fuzzy neur...