Recently, enormous datasets have made power dissipation and area usage lie at the heart
of designs for artificial neural networks (ANNs). Considering the significant role of activation …

This paper studies the effects of adversarial attacks on Deep Neural Networks (DNN)
constructed using memristor crossbar arrays and analog components. The presented …

Artificial neural networks (ANNs) have recently made a significant impact on the field of
industrial electronics. Increasing efforts have been focused on implementing ANN using …

Metaverse is an initiative, an immersive virtual-reality (VR) digital space that installs to the
next-generation Internet for a platform of network human–computer interaction mode. As the …

It is shown that compressed learning tolerates adversarial attacks effectively and that
classification accuracy is impacted minimally when the compression ratio is selected …

Recent studies have shown that Memristor Crossbar Array (MCA)-based Deep Neural
Network (DNN) accelerators are resilient to adversarial attacks. This paper shows that …

This paper shows that Memristive Crossbar Array (MCA)-based neuromorphic architectures
provide a robust defense against adversarial attacks due to the stochastic behavior of …

This paper shows that input preprocessing using compression and subsequent rescale and
rearrange operations implemented using Memristor Crossbar Arrays (MCAs) provides a …

Over the past thirty years, the idea of computing based on models inspired by human brains
and biological neural networks emerged. Artificial neural networks play an important role in …

This paper shows the learnability of complex Boolean Logic functions by Deep Neural
Networks (DNNs) and the ability to accelerate logic evaluation using DNNs while ensuring …