Spiking Neural Networks (SNNs) have high potential to process information efficiently with
binary spikes and time delay information. Recently, dedicated SNN hardware accelerators …

In this paper, we explore efficient hardware implementation of feedforward artificial neural
networks (ANNs) using approximate adders and multipliers. Due to a large area requirement …

This article presents design techniques proposed for efficient hardware implementation of
feedforward artificial neural networks (ANNs) under parallel and time-multiplexed …

This work addresses a structure optimization of neuromorphic computing architectures. This
enables to speed up the computation of fully connected neural network twice as fast as …

In this paper, we propose an efficient method to realize a convolution layer of the
convolution neural networks (CNNs). Inspired by the fully-connected neural network …

This paper presents hardware-aware training techniques for efficient hardware
implementation of feedforward artificial neural networks (ANNs). Firstly, an investigation is …