As data processing volume increases, the limitations of traditional computers and the need
for more efficient computing methods become evident. Neuromorphic computing mimics the …

Biological neural networks continue to inspire new developments in algorithms and
microelectronic hardware to solve challenging data processing and classification problems …

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 …

Several analog and digital brain-inspired electronic systems have been recently proposed
as dedicated solutions for fast simulations of spiking neural networks. While these …

The ever‐increasing processing power demands of digital computers cannot continue to be
fulfilled indefinitely unless there is a paradigm shift in computing. Neuromorphic computing …

This paper proposes a neuromorphic platform for on-FPGA online spike timing dependant
plasticity (STDP) learning, based on the COordinate Rotation DIgital Computer (CORDIC) …

Although data processing technology continues to advance at an astonishing rate,
computers with brain-like processing capabilities still elude us. It is envisioned that such …

The ability to carry out signal processing, classification, recognition, and computation in
artificial spiking neural networks (SNNs) is mediated by their synapses. In particular, through …

Understanding how biological neural networks carry out learning using spike-based local
plasticity mechanisms can lead to the development of real-time, energy-efficient, and …

In designing neuromorphic circuits and systems, developing compact and energy-efficient
neuron and synapse circuits is essential for high-performance on-chip neural architectures …