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We present a novel family of continuous, linear time-frequency transforms adaptable to a multitude of (nonlinear) frequency scales. Similar to classical time-frequency or time-scale representations, the representation coefficients are…

Functional Analysis · Mathematics 2024-03-20 Nicki Holighaus , Christoph Wiesmeyr , Peter Balazs

Estimating many local expectation values over time is a central measurement bottleneck in quantum simulation and device characterization. We study the task of reconstructing the Pauli-signal matrix $S_{ij}=\text{Tr}(O_i \rho(t_j))$ for a…

Quantum Physics · Physics 2026-02-16 Joseph Barreto , Daniel Lidar

Time-fluctuating signals are ubiquitous and diverse in many physical, chemical, and biological systems, among which random telegraph signals (RTSs) refer to a series of instantaneous switching events between two discrete levels from…

Applied Physics · Physics 2022-06-02 Marcel Robitaille , HeeBong Yang , Lu Wang , Na Young Kim

Compressive sensing (CS) can effectively recover a signal when it is sparse in some discrete atoms. However, in some applications, signals are sparse in a continuous parameter space, e.g., frequency space, rather than discrete atoms.…

Signal Processing · Electrical Eng. & Systems 2018-08-30 Tianyao Huang , Yimin Liu , Huadong Meng , Xiqin Wang

A new class of spatially-coupled turbo-like codes (SC-TCs), dubbed generalized spatially coupled parallel concatenated codes (GSC-PCCs), is introduced. These codes are constructed by applying spatial coupling on parallel concatenated codes…

Information Theory · Computer Science 2022-02-25 Min Qiu , Xiaowei Wu , Jinhong Yuan , Alexandre Graell i Amat

Asynchronous Time Series is a multivariate time series where all the channels are observed asynchronously-independently, making the time series extremely sparse when aligning them. We often observe this effect in applications with complex…

Machine Learning · Computer Science 2022-08-25 Vijaya Krishna Yalavarthi , Johannes Burchert , Lars Schmidt-Thieme

Compressive sensing achieves effective dimensionality reduction of signals, under a sparsity constraint, by means of a small number of random measurements acquired through a sensing matrix. In a signal processing system, the problem arises…

Information Theory · Computer Science 2014-03-13 Diego Valsesia , Enrico Magli

The N = 2, 4 superconformal symmetry constraints in d = 4 for four point functions of chiral primary 1/2-BPS operators are derived. The operators are described by symmetric traceless tensors of the internal R-symmetry group. A substantial…

High Energy Physics - Theory · Physics 2017-06-06 Michael Nirschl

Motivated by quantum gravity and the CFT Distance Conjecture, we study infinite-distance limits in four-dimensional ${\cal N}=2$ superconformal field theories with higher-dimensional conformal manifolds and their AdS duals. We focus on…

High Energy Physics - Theory · Physics 2026-03-04 Fabio Mantegazza , Enrico Marchetto , Elli Pomoni , Torben Skrzypek , Timo Weigand

Coherent multi-transducer ultrasound (CoMTUS) creates an extended effective aperture through the coherent combination of multiple arrays, which results in images with enhanced resolution, extended field-of-view, and higher sensitivity. The…

Recent development in compressed sensing (CS) has revealed that the use of a special design of measurement matrix, namely the spatially-coupled matrix, can achieve the information-theoretic limit of CS. In this paper, we consider the…

Information Theory · Computer Science 2014-02-14 Chao-Kai Wen , Kai-Kit Wong

This invention addresses fixed-point representations of convolutional neural networks (CNN) in integrated circuits. When quantizing a CNN for a practical implementation there is a trade-off between the precision used for operations between…

Neural and Evolutionary Computing · Computer Science 2018-07-27 Mo'taz Al-Hami , Marcin Pietron , Rishi Kumar , Raul A. Casas , Samer L. Hijazi , Chris Rowen

In cosparse analysis compressive sensing (CS), one seeks to estimate a non-sparse signal vector from noisy sub-Nyquist linear measurements by exploiting the knowledge that a given linear transform of the signal is cosparse, i.e., has…

Information Theory · Computer Science 2014-10-21 Mark Borgerding , Philip Schniter , Sundeep Rangan

A positive integer is expressed as a sum of squares of positive integers in a unique way applying a special technique. The expression, thus obtained is resolved into two factors using the concept of the Clifford algebra. This technique is…

General Mathematics · Mathematics 2012-09-19 Amitabha Chanda

This paper presents a general and systematic discussion of various symbolic representations of iterated maps through subshifts. We give a unified model for all continuous maps on a metric space, by representing a map through a general…

Chaotic Dynamics · Physics 2007-05-23 Xin-Chu Fu , Weiping Lu , Peter Ashwin , Jinqiao Duan

The application of nonlinear transformations to a cyclostationary signal for the purpose of revealing hidden periodicities has proven to be useful for applications requiring signal selectivity and noise tolerance. The fact that the hidden…

Information Theory · Computer Science 2023-07-19 Chia Wei Lim , Michael B. Wakin

This work explores the representation of univariate and multivariate functions as matrix product states (MPS), also known as quantized tensor-trains (QTT). It proposes an algorithm that employs iterative Chebyshev expansions and Clenshaw…

Time-frequency distributions have been used to provide high resolution representation in a large number of signal processing applications. However, high resolution and accurate instantaneous frequency (IF) estimation usually depend on the…

Information Theory · Computer Science 2015-03-02 Irena Orovic , Andjela Draganic , Srdjan Stankovic

In~\cite{sic-magazine-2025}, the authors show that the square index coefficients (SICs) of the $N$-point discrete Fourier transform (DFT) -- that is, the coefficients $X_{k\sqrt{N}}$ for $k = 0, 1, \ldots, \sqrt{N} - 1$ -- can be losslessly…

Signal Processing · Electrical Eng. & Systems 2025-05-06 Saulo Queiroz , João P. Vilela , Benjamin Koon Kei Ng , Chan-Tong Lam , Edmundo Monteiro

Quadrature compressive sampling (QuadCS) is a sub-Nyquist sampling scheme for acquiring in-phase and quadrature (I/Q) components in radar. In this scheme, the received intermediate frequency (IF) signals are expressed as a linear…

Information Theory · Computer Science 2015-03-03 Feng Xi , Shengyao Chen , Yimin D. Zhang , Zhong Liu
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