The rapid development of artificial intelligence (AI) demands the rapid development of
domain-specific hardware specifically designed for AI applications. Neuro-inspired …

The volume, veracity, variability, and velocity of data produced from the ever increasing
network of sensors connected to Internet pose challenges for power management …

PyTorch is a library for Python programs that encourages deep learning programs. With this
receptiveness and convenience found in (Deep Learning for Computer Vision: Expert …

The on-chip implementation of learning algorithms would speed up the training of neural
networks in crossbar arrays. The circuit level design and implementation of a back …

We present both an overview and a perspective of recent experimental advances and
proposed new approaches to performing computation using memristors. A memristor is a 2 …

The high performance requirements of nowadays computer networks are limiting their ability
to support important requirements of the future. Two important properties essential in …

Current advances in emerging memory technologies enable novel and unconventional
computing architectures for high-performance and low-power electronic systems, capable of …

This article investigates hardware implementation of hierarchical temporal memory (HTM), a
brain-inspired machine learning algorithm that mimics the key functions of the neocortex and …

Memristor crossbar architecture is one of the most popular circuit configurations due to its
wide range of practical applications. The crossbar architecture can emulate the weighted …

The memristive crossbar aims to implement analog weighted neural network, however, the
realistic implementation of such crossbar arrays is not possible due to limited switching …