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Bandpass signals are an important sub-class of bandlimited signals that naturally arise in a number of application areas but their high-frequency content poses an acquisition challenge. Consequently, "Bandpass Sampling Theory" has been…

Information Theory · Computer Science 2023-07-12 Gal Shtendel , Dorian Florescu , Ayush Bhandari

Shannon's sampling theorem is one of the cornerstone topics that is well understood and explored, both mathematically and algorithmically. That said, practical realization of this theorem still suffers from a severe bottleneck due to the…

Information Theory · Computer Science 2020-12-02 Ayush Bhandari , Felix Krahmer , Ramesh Raskar

The Unlimited Sensing Framework (USF) is a digital acquisition protocol that allows for sampling and reconstruction of high dynamic range signals. By acquiring modulo samples, the USF circumvents the clipping or saturation problem that is a…

Information Theory · Computer Science 2022-07-28 Ayush Bhandari

In this paper, we address the problem of reconstructing multiband signals from modulo-folded, pointwise samples within the Unlimited Sensing Framework (USF). Focusing on a low-complexity, single-channel acquisition setup, we establish…

Signal Processing · Electrical Eng. & Systems 2025-11-03 Gal Shtendel , Ayush Bhandari

Analog-to-digital converters (ADCs) play a critical role in digital signal acquisition across various applications, but their performance is inherently constrained by sampling rates and bit budgets. This bit budget imposes a trade-off…

Signal Processing · Electrical Eng. & Systems 2025-09-10 Vaclav Pavlicek , Ayush Bhandari

In this paper, we investigate the relationship between the dynamic range and quantization noise power in modulo analog-to-digital converters (ADCs). Two modulo ADC systems are considered: (1) a modulo ADC which outputs the folded samples…

Signal Processing · Electrical Eng. & Systems 2025-09-03 Neil Irwin Bernardo , Shaik Basheeruddin Shah , Yonina C. Eldar

Following the Unlimited Sampling strategy to alleviate the omnipresent dynamic range barrier, we study the problem of recovering a bandlimited signal from point-wise modulo samples, aiming to connect theoretical guarantees with hardware…

Information Theory · Computer Science 2022-04-06 Ayush Bhandari , Felix Krahmer , Thomas Poskitt

Digital acquisition of high bandwidth signals is particularly challenging when Nyquist rate sampling is impractical. This has led to extensive research in sub-Nyquist sampling methods, primarily for spectral and sinusoidal frequency…

Information Theory · Computer Science 2024-09-26 Ruiming Guo , Yuliang Zhu , Ayush Bhandari

Two important attributes of analog to digital converters (ADCs) are its sampling rate and dynamic range. The sampling rate should be greater than or equal to the Nyquist rate for bandlimited signals with bounded energy. It is also desired…

Signal Processing · Electrical Eng. & Systems 2021-10-08 Eyar Azar , Satish Mulleti , Yonina C. Eldar

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…

Signal Processing · Electrical Eng. & Systems 2023-07-03 Thomas Feuillen , Bhavani Shankar MRR , Ayush Bhandari

The Unlimited Sensing Framework (USF) was recently introduced to overcome the sensor saturation bottleneck in conventional digital acquisition systems. At its core, the USF allows for high-dynamic-range (HDR) signal reconstruction by…

Information Theory · Computer Science 2022-02-16 Dorian Florescu , Felix Krahmer , Ayush Bhandari

The recovery of bandlimited signals with high dynamic range is a hot issue in sampling research. The unlimited sampling theory expands the recordable range of traditional analog-to-digital converters (ADCs) arbitrarily, and the signal is…

Signal Processing · Electrical Eng. & Systems 2023-02-20 Hui Zhao , Bing-Zhao Li

There have been a number of studies on sparse signal recovery from one-bit quantized measurements. Nevertheless, little attention has been paid to the choice of the quantization thresholds and its impact on the signal recovery performance.…

Information Theory · Computer Science 2013-05-21 Jun Fang , Yanning Shen , Hongbin Li

Representing a continuous-time signal by a set of samples is a classical problem in signal processing. We study this problem under the additional constraint that the samples are quantized or compressed in a lossy manner under a limited…

Information Theory · Computer Science 2018-04-12 Alon Kipnis , Yonina C. Eldar , Andrea J. Goldsmith

Sampling theories lie at the heart of signal processing devices and communication systems. To accommodate high operating rates while retaining low computational cost, efficient analog-to digital (ADC) converters must be developed. Many of…

Information Theory · Computer Science 2010-10-12 Moslem Rashidi

We study Sigma-Delta quantization methods coupled with appropriate reconstruction algorithms for digitizing randomly sampled low-rank matrices. We show that the reconstruction error associated with our methods decays polynomially with the…

Information Theory · Computer Science 2018-04-18 Eric Lybrand , Rayan Saab

We study the problem of approximately recovering signals on a manifold from one-bit linear measurements drawn from either a Gaussian ensemble, partial circulant ensemble, or bounded orthonormal ensemble and quantized using Sigma-Delta or…

Information Theory · Computer Science 2019-04-25 Mark Iwen , Eric Lybrand , Aaron Nelson , Rayan Saab

Conventional analog-to-digital converters (ADCs) clip when signals exceed their input range. Modulo (unlimited) sampling overcomes this limitation by folding the signal before digitization, but existing recovery methods are either…

Signal Processing · Electrical Eng. & Systems 2025-09-17 Wenyi Yan , Zeyuan Li , Lu Gan , Honqing Liu , Guoquan Li

In the paper, we consider the line spectral estimation problem in an unlimited sensing framework (USF), where a modulo analog-to-digital converter (ADC) is employed to fold the input signal back into a bounded interval before quantization.…

Signal Processing · Electrical Eng. & Systems 2024-08-14 Hongwei Wang , Jun Fang , Hongbin Li , Geert Leus

Conventional digitization based on the Shannon-Nyquist method, implemented via analog-to-digital converters (ADCs), faces fundamental limitations. High-dynamic-range (HDR) signals often get clipped or saturated in practice. Given a fixed…

Signal Processing · Electrical Eng. & Systems 2024-10-29 Yuliang Zhu , Ayush Bhandari
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