10 accepted papers
Mainstream signal processing theory and methods are primarily designed for synchronous sampling architectures, where samples are captured at predefined time instants. While this fits well with Shannon’s framework, in the absence of synchronous structure, even fundamental tools like filtering and con…
Estimating frequencies of damped sinusoids is the underlying problem of many practical applications. Existing algorithms are often inaccurate for estimating frequencies from damped sinusoids since many of them are designed for undamped signals. In this paper we propose an algorithm to estimate frequ…
The problem of sub-Nyquist multiband sensing has numerous applications across various fields. Despite substantial algorithmic pursuits, the practical implementation of these methods is subject to limitations of digital acquisition via analog-to-digital converters (ADCs). Multiband reconstruction for…
Recovering multiband spectra from sub-Nyquist sampling is a prominent research area in signal processing, driven by its wide range of applications and the technical challenges it presents. These challenges demand novel algorithmic approaches tailored to specific scenarios. The problem becomes even m…
The problem of frequency estimation from sub-Nyquist samples has numerous applications across various disciplines and has been extensively studied in signal processing literature. Despite the existence of several algorithmic approaches, the full potential of these methods has not been realized due t…
Recently, contrastive multi-view clustering (MvC) has emerged as a promising avenue for analyzing data from heterogeneous sources, typically leveraging the off-the-shelf instances as positives and randomly sampled ones as negatives. In practice, however, this paradigm would unavoidably suffer from t…
Unlimited Sampling Framework (USF) is a digital acquisition protocol that recovers high dynamic range (HDR) input signals from their low dynamic range, modulo samples. Current USF theory and algorithms are predominantly focused on bandlimited signal classes that rely on a relatively high sampling ra…
To achieve High Dynamic Range (HDR) sensing, the Unlimited Sampling Framework (USF) was recently proposed. In the USF, modulo encoding of the continuous-time input signal prevents the analog-to- digital converter (ADC) from saturation. For recovering the HDR signal from folded samples, reconstructio…
Deep learning methods have witnessed the great progress in image restoration with specific metrics (e.g., PSNR, SSIM). However, the perceptual quality of the restored image is relatively subjective, and it is necessary for users to control the reconstruction result according to personal preferences…
While sensors have been widely used in various applications, an essential current trend of research consists of collecting and fusing the information that comes from many sensors. In this paper, on the contrary, we would like to concentrate on a unique mobile sensor; our goal is to unveil the multid…