Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices,
and models that contrast the pervasive von Neumann computer architecture. This …

It is already true that Big Data has drawn huge attention from researchers in information
sciences, policy and decision makers in governments and enterprises. As the speed of …

In this article, the problem of the global Mittag-Leffler synchronization is proposed for a sort
of discrete-time fractional-order neural networks (DFNNs) with delays. In the first place, a …

The investigation of the human intelligence, cognitive systems and functional complexity of
human brain is significantly facilitated by high-performance computational platforms. In this …

The compliant nature of soft fingers allows for safe and dexterous manipulation of objects by
humans in an unstructured environment. A soft prosthetic finger design with tactile sensing …

Due to the ability to implement customized topology, FPGA is increasingly used to deploy
SNNs in both embedded and high-performance applications. In this paper, we survey state …

There has been a strong push recently to examine biological scale simulations of
neuromorphic algorithms to achieve stronger inference capabilities. This paper presents a …

In this paper, we present the parallel neuromorphic processor architectures for spiking
neural networks on FPGA. The proposed architectures address several critical issues …

We present a design framework for neuromorphic architectures in the nano-CMOS era. Our
approach to the design of spiking neurons and STDP learning circuits relies on parallel …

The neuron can be called the main cell of a nervous system that can transmit messages from
one neuron to another neuron or another cell through electrical signals. In neuromorphic …