For the last few years, one can see the emergence of a large number of intelligent products
and services, their commercial availability and the socioeconomic impact, this raises the …

Current studies on non-systematic satisfiability in Discrete Hopfield Neural Network are able
to avoid production of repetitive final neuron states which improves the quality of global …

The superconductor single flux quantum (SFQ) logic family has been recognized as a
promising candidate to resolve the energy consumption crisis in the post-Moore era, owing …

Intuitively, artificial intelligence, robotics, and information and communication technologies
are important because they give enterprises and institutions insights into their operations …

Our brain can with ease recognize images despite size variance, a capability that has been
attributed to the normalization of images and feature extraction by biological computational …

An approach for the recognition of low resolution grey scale facial images using cloud
Hopfield neural network (CHNN) is presented. This approach consists of three steps: first we …

Hopfield model (HM) classified under the category of recurrent networks has been used for
pattern retrieval and solving optimization problems. This network acts like a CAM (content …

Abstract The Traveling Salesman Problem (TSP) is one of the most notorious challenges in
the fields of optimization and operation research. The TSP asks an apparently easy …

Photoelectrochemical (PEC) cells have a great potential as a source of green energy, but it
is a major challenge to make energy efficient, durable and cheap PEC cells. There are still …

The superconductor single flux quantum (SFQ) logic family has been recognized as a
promising candidate to resolve the energy consumption crisis in the post-Moore era, owing …