The design of robots that interact autonomously with the environment and exhibit complex
behaviours is an open challenge that can benefit from understanding what makes living …

In individuals with sensory-motor impairments, missing limb functions can be restored using
neuroprosthetic devices that directly interface with the nervous system. However, restoring …

Neuromorphic processing systems implementing spiking neural networks with mixed signal
analog/digital electronic circuits and/or memristive devices represent a promising …

Classical sampling is based on acquiring signal amplitudes at specific points in time, with
the minimal sampling rate dictated by the degrees of freedom in the signal. The samplers in …

Bioelectronic medicine treats chronic diseases by sensing, processing, and modulating the
electronic signals produced in the nervous system of the human body, labeled'neural …

Condition monitoring signals provide sufficient information about the health of machines
and, therefore, are widely used for fault diagnosis, prognosis, and health management …

Increasing complexity and data-generation rates in cyber-physical systems and the
industrial Internet of things are calling for a corresponding increase in AI capabilities at the …

Time-based sampling of continuous-time signals is an alternative to Shannon's sampling
paradigm in which the signal is encoded using a sequence of nonuniform time instants. The …

In this article we examine recent developments in the research area concerning the creation
of end-to-end models for the complete optimization of measuring instruments. The models …

We address the problem of 3-D reconstruction using neuromorphic cameras (also known as
event-driven cameras), which are a new class of vision-inspired imaging devices …