Nowadays, being in digital era the data generated by various applications are increasing
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …

As semiconductor technology enters the more than Moore era, there exists an apparent
contradiction between the rapidly growing demands for data processing and the visible …

The neuron models have been widely applied to neuromorphic computing systems and
chaotic circuits. However, discrete neuron models and their application in image encryption …

To tackle important combinatorial optimization problems, a variety of annealing-inspired
computing accelerators, based on several different technology platforms, have been …

At present, machine learning systems use simplified neuron models that lack the rich
nonlinear phenomena observed in biological systems, which display spatio-temporal …

We present a simple yet highly dimensional hybrid diode bridge circuit network that can
exhibit complex chaotic behaviours. Further, since our network is characterised by smooth …

The nonlinear characteristics are studied in a new 4D Hopfield neural network model with
two nonlinear synaptic weights in this paper. The synaptic function is modeled by …

This paper surveys main principles of feature selection and their recent applications in big
data bioinformatics. Instead of the commonly used categorization into filter, wrapper, and …

Metaheuristics are the most exciting development in approximate optimization techniques of
the last two decades. They have had widespread successes in attacking a variety of difficult …

The search for chaotic patterns has occupied numerous investigators in neuroscience, as in
many other fields of science. Their results and main conclusions are reviewed in the light of …