We present the results of the comparative performance-versus-complexity analysis for the
several types of artificial neural networks (NNs) used for nonlinear channel equalization in …

Next-generation mobile networks are expected to meet the requirements of a wide range of
new vertical services. Hence, the network slicing concept has been introduced, in which …

This paper presents novel reconfigurable architectures for reducing the latency of recurrent
neural networks (RNNs) that are used for detecting gravitational waves. Gravitational …

This article presents a reconfigurable accelerator for REcurrent Neural networks with fine-
grained cOlumn-Wise matrix–vector multiplicatioN (RENOWN). We propose a novel latency …

In this paper, a novel relaying scheme is proposed for bipolar line commutated converter
(LCC) high voltage direct current (HVDC) transmission lines that detects the fault, identifies …

Multidimensional Long Short-Term Memory (MD-LSTM) neural network is an extension of
one-dimensional LSTM for data with more than one dimension. MD-LSTM achieves state-of …

This work introduces Remarn, a reconfigurable multi-threaded multi-core accelerator
supporting both spatial and temporal co-execution of Recurrent Neural Network (RNN) …

Neural networks have demonstrated their outstanding performance in a wide range of tasks.
Specifically recurrent architectures based on long-short term memory (LSTM) cells have …

Complex-valued double-sideband direct detection (DD) can reconstruct the optical field and
achieve a high electrical spectral efficiency (ESE) comparable to that of a coherent …

Network slicing is one of the cornerstones for next-generation mobile communication
systems. Specifically, it enables Mobile Virtual Network Operators (MVNOs) to offer various …