23 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…
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…
Bandpass signals are fundamental to a number of applications. Such signal classes are characterized by high-frequency content. Thus, their digital acquisition is demanding due to the higher sampling rate requirement. Relaxing this requirement has been widely investigated in the literature in the con…
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…
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…
In this paper, the trade-off between the quantization noise and the dynamic range of ADCs used to acquire radar signals is revisited using the Unlimited Sensing Framework (USF) in a practical setting. Trade-offs between saturation and resolution arise in many applications, like radar, where sensors…
The Unlimited Sampling Framework (USF) is an alternative sampling and reconstruction protocol that allows for recovery of signals that are arbitrarily larger than the dynamic range of the analog-to-digital converter (ADC). In the USF, modulo non-linearity prior to sampling folds high dynamic range i…
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…
In event-driven sampling (EDS) the signal is represented in terms of a series of spikes at non-uniform time locations. Owing to the limited dynamic range (DR), just like how conventional analog-to-digital converters (ADC) suffer from signal saturation, in EDS a similar manifestation is observed. Nam…
Signal saturation or clipping is a fundamental bottleneck that limits the capability of analog-to-digital converters (ADCs). The problem arises when the input signal dynamic range is larger than ADC’s dynamic range. To overcome this issue, an alternative acquisition protocol called the Unlimited Sen…
Unlimited Sensing is a sampling protocol that recovers high dynamic range input signals from their low dynamic range, modulo samples. Bridging the gap between theory and practice, recently, a hardware validation of the unlimited sampling method was presented. Taking another step in this direction, i…
In contrast to Shannon sampling theory, where measurements are recorded at equally-spaced time instants, event-driven sampling records values at non-uniform instants dependent on the input. However, both sampling schemes are subject to input dynamic range constraints. This represents a fundamental b…
The fractional Fourier transform has found applications in a variety of topics linked with science and engineering. In this context, sampling theory is one of the most well-studied subjects. Since the fractional Fourier transform or the FrFT generalizes the notion of bandlimitedness, extension of Sh…
Conventional analog-to-digital converters (ADCs) are limited in dynamic range. If a signal exceeds some prefixed threshold, the ADC saturates and the resulting signal is clipped, thus becoming prone to aliasing artifacts. Recent developments in ADC design allow to overcome this limitation: using mod…
Super-resolution is the art of recovering spikes from their low-pass projections. Over the last decade specifically, several significant advancements linked with mathematical guarantees and recovery algorithms have been made. Most super-resolution algorithms rely on a two-step procedure: deconvoluti…
In a recent paper [1], we introduced the concept of “Unlimited Sampling”. This unique approach circumvents the clipping or saturation problem in conventional analog-to-digital converters (ADCs) by considering a radically different ADC architecture which resets the input voltage before saturation. Su…
The field of signal processing is replete with exemplary problems where the measurements amount to time-delayed and amplitude scaled echoes of some template function or a pulse. When the inter-pulse spacing is favorable, something as primitive as a matched filter serves the purpose of identifying ti…
This paper considers the problem of sampling and reconstruction of a continuous-time sparse signal without assuming the knowledge of the sampling instants or the sampling rate. This topic has its roots in the problem of recovering multiple echoes of light from its low-pass filtered and auto-correlat…
Finite-Rate-of-Innovation (FRI) sampling theory prescribes a procedure for exact recovery of Dirac impulses from linear measurements in the form of orthogonal projections of streams of Dirac impulses onto the subspace of Fourier—bandlimited functions. This enables recovery of a continuous time spars…
Optical time-of-flight (ToF) sensors can measure scene depth accurately by projection and reception of an optical signal. The range to a surface in the path of the emitted signal is proportional to the delay time of the light echo or the reflected signal. In practice, a diverging beam may be subject…
When multiple light paths combine at a given location on an image sensor, an image mixture is created. Demixing or recovering the original constituent components in such cases is a highly ill-posed problem. A number of elegant solutions have thus been developed in the literature, relying on measurem…
This work considers the problem of super-resolution. The goal is to resolve a Dirac distribution from knowledge of its discrete, low-pass, Fourier measurements. Classically, such problems have been dealt with parameter estimation methods. Recently, it has been shown that convex-optimization based fo…