This paper presents a 64× 2 channel stereo-audio sensing front end with parallel
asynchronous event output inspired by the biological cochlea. Each binaural channel …

Energy-constrained biomedical recording systems need power-efficient data converters and
good signal compression in order to meet the stringent power consumption requirements of …

Analog feature extraction (AFE) is an appealing strategy for low-latency and efficient
cognitive sensing systems since key features are much sparser than the Nyquist-sampled …

Finding new data acquisition methods for practical instrumentation development which can
be used in case of monitoring purposes of aerospace RF spectrum are a key research area …

Feature extraction, such as spectral occupancy, interferer energy and type, or direction-of-
arrival, from wideband radio-frequency (RF) signals finds use in a growing number of …

Analog-to-Information Converters (AICs) represent the implementation of the Compressed
Sensing theory in practice. An AIC is a device that takes as input an analog signal and …

In recent years, Neural networks (NNs) present vast potential for innovative applications.
However, energy efficiency continues to remain a challenge in deploying NNs on the edge …

In this work, the problem of signal parameter estimation from measurements acquired by a
low-complexity analog-to-digital converter (ADC) with 1-bit output resolution and an …

Over the past decade, the successive approximation register (SAR) architecture has played
a significant role in advancing the state of the art in analog-to-digital conversion. One of the …

The installation of smart meters is fast growing to effectively support various smart grid stack
holders. Collection and processing of fine-grained metering data is important for proper …