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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

In this paper we introduce a new sampling and reconstruction approach for multi-dimensional analog signals. Building on top of the Unlimited Sensing Framework (USF), we present a new folded sampling operator called the multi-dimensional…

Information Theory · Computer Science 2022-09-15 Dorian Florescu , 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

An alternative to conventional uniform sampling is that of time encoding, which converts continuous-time signals into streams of trigger times. This gives rise to Event-Driven Sampling (EDS) models. The data-driven nature of EDS acquisition…

Information Theory · Computer Science 2022-10-11 Dorian Florescu , Ayush Bhandari

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

The problem of sparse multichannel blind deconvolution (S-MBD) arises frequently in many engineering applications such as radar/sonar/ultrasound imaging. To reduce its computational and implementation cost, we propose a compression method…

Signal Processing · Electrical Eng. & Systems 2023-07-05 Bahareh Tolooshams , Satish Mulleti , Demba Ba , Yonina C. Eldar

The latest theoretical advances in the field of unlimited sampling framework (USF) show the potential to avoid clipping problems of analog-to-digital converters (ADC). To date, most of the related works have focused on real-valued modulo…

Signal Processing · Electrical Eng. & Systems 2020-12-01 Yan He , Jifang Qiu , Chang Liu , Yue Liu , Jian Wu

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

Analog-to-Digital Converters (ADCs) are essential components in modern data acquisition systems. A key design challenge is accommodating high dynamic range (DR) input signals without clipping. Existing solutions, such as oversampling,…

Signal Processing · Electrical Eng. & Systems 2024-12-18 Shaik Basheeruddin Shah , Satish Mulleti , Yonina C. Eldar

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

We consider the problem of recovering a continuous-time bandlimited signal from the discrete-time signal obtained from sampling it every $T_s$ seconds and reducing the result modulo $\Delta$, for some $\Delta>0$. For $\Delta=\infty$ the…

Information Theory · Computer Science 2021-09-21 Elad Romanov , Or Ordentlich

Finite Rate of Innovation (FRI) sampling theory enables reconstruction of classes of continuous non-bandlimited signals that have a small number of free parameters from their low-rate discrete samples. This task is often translated into a…

Signal Processing · Electrical Eng. & Systems 2023-07-21 Vincent C. H. Leung , Jun-Jie Huang , Yonina C. Eldar , Pier Luigi Dragotti

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

Analog-to-digital converters (ADCs) play a vital important role in any devices via manipulating analog signals in a digital manner. Given that the amplitude of the signal exceeds the dynamic range of the ADCs, clipping occurs and the…

Signal Processing · Electrical Eng. & Systems 2024-10-28 Jiang Zhu , Junnan Ma , Zhenlong Liu , Fengzhong Qu , Zheng Zhu , Qi Zhang

In high-dynamic range (HDR) analog-to-digital converters (ADCs), having many quantization bits minimizes quantization errors but results in high bit rates, limiting their application scope. A strategy combining modulo-folding with a low-DR…

Signal Processing · Electrical Eng. & Systems 2023-11-23 Satish Mulleti , Resham Yashwanth Kumar , Laxmeesha Somappa

The need to recover high-dimensional signals from their noisy low-resolution quantized measurements is widely encountered in communications and sensing. In this paper, we focus on the extreme case of one-bit quantizers, and propose a deep…

Signal Processing · Electrical Eng. & Systems 2021-11-10 Shahin Khobahi , Nir Shlezinger , Mojtaba Soltanalian , Yonina C. Eldar

Sampling shift-invariant (SI) signals with a high dynamic range poses a notable challenge in the domain of analog-to-digital conversion (ADC). It is essential for the ADC's dynamic range to exceed that of the incoming analog signal to…

Signal Processing · Electrical Eng. & Systems 2024-06-18 Yhonatan Kvich , Yonina C. Eldar

Analog to digital converters (ADCs) act as a bridge between the analog and digital domains. Two important attributes of any ADC are sampling rate and its dynamic range. For bandlimited signals, the sampling should be above the Nyquist rate.…

Signal Processing · Electrical Eng. & Systems 2022-06-30 Eyar Azar , Satish Mulleti , Yonina C. Eldar

Many modern applications involve the acquisition of noisy modulo samples of a function $f$, with the goal being to recover estimates of the original samples of $f$. For a Lipschitz function $f:[0,1]^d \to \mathbb{R}$, suppose we are given…

Statistics Theory · Mathematics 2021-05-04 Michaël Fanuel , Hemant Tyagi

In this paper, utilizing techniques in compressed sensing, parallel optimization and deep learning, we propose a model-driven approach to jointly design the common measurement matrix and GROUP LASSO-based jointly sparse signal recovery…

Information Theory · Computer Science 2020-02-10 Shuaichao Li , Wanqing Zhang , Ying Cui
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