Artificial intelligence (AI) is accelerating the development of unconventional computing
paradigms inspired by the abilities and energy efficiency of the brain. The human brain …

Reservoir computing is a computational framework suited for temporal/sequential data
processing. It is derived from several recurrent neural network models, including echo state …

Reservoir computing systems utilize dynamic reservoirs having short-term memory to project
features from the temporal inputs into a high-dimensional feature space. A readout function …

The booming development of artificial intelligence (AI) requires faster physical processing
units as well as more efficient algorithms. Recently, reservoir computing (RC) has emerged …

With the advent of artificial intelligence (AI), memristors have received significant interest as
a synaptic building block for neuromorphic systems, where each synaptic memristor should …

Reservoir computing was achieved by constructing a network of virtual nodes multiplexed in
time and sharing a single silicon beam exhibiting a classical Duffing non-linearity as the …

Due to the complexity of real environments, it is hard to detect toxic and harmful gases by
sensors. To address such an issue, an artificial olfactory system is promoted, emulating the …

In this paper, we propose a novel computational architecture of memristor-based echo state
network (MESN) with the online least mean square (LMS) algorithm. Newman and Watts …

Despite its prevalence in neurosensory systems for pattern recognition, event detection, and
learning, the effects of sensory adaptation (SA) are not explored in reservoir computing …

During the past two decades, epileptic seizure detection and prediction algorithms have
evolved rapidly. However, despite significant performance improvements, their hardware …