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A considerable amount of research in harmonic analysis has been devoted to non-linear estimators of signals contaminated by additive Gaussian noise. They are implemented by thresholding coefficients in a frame, which provide a sparse signal…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Nathanaël Cuvelle--Magar , Stéphane Mallat

Modeling sequential data has become more and more important in practice. Some applications are autonomous driving, virtual sensors and weather forecasting. To model such systems so called recurrent models are used. In this article we…

Machine Learning · Statistics 2017-11-21 Roman Föll , Bernard Haasdonk , Markus Hanselmann , Holger Ulmer

We consider the problem of recovering the support of a sparse signal using noisy projections. While extensive work has been done on the dense measurement matrix setting, the sparse setting remains less explored. In this work, we establish…

Machine Learning · Statistics 2025-09-03 Youssef Chaabouni , David Gamarnik

Consider a waveform channel where the transmitted signal is corrupted by Wiener phase noise and additive white Gaussian noise (AWGN). A discrete-time channel model that takes into account the effect of filtering on the phase noise is…

Information Theory · Computer Science 2013-01-30 Hassan Ghozlan , Gerhard Kramer

We present the framework of slowly varying regression under sparsity, allowing sparse regression models to exhibit slow and sparse variations. The problem of parameter estimation is formulated as a mixed-integer optimization problem. We…

Machine Learning · Computer Science 2023-11-14 Dimitris Bertsimas , Vassilis Digalakis , Michael Linghzi Li , Omar Skali Lami

For a generalized Su-Schrieffer-Heeger model the energy zero is always critical and hyperbolic in the sense that all reduced transfer matrices commute and have their spectrum off the unit circle. Disorder driven topological phase…

Mathematical Physics · Physics 2023-05-03 Joris De Moor , Christian Sadel , Hermann Schulz-Baldes

Suppose ${\bf x}$ is any exactly $k$-sparse vector in $\mathbb{C}^{n}$. We present a class of phase measurement matrix $A$ in $\mathbb{C}^{m\times n}$, and a corresponding algorithm, called SUPER, that can resolve ${\bf x}$ up to a global…

Information Theory · Computer Science 2014-01-28 Sheng Cai , Mayank Bakshi , Sidharth Jaggi , Minghua Chen

The density matrix renormalization group method is used to investigate the spin-Peierls transition for Heisenberg spins coupled to quantized phonons. We use a phonon spectrum that interpolates between a gapped, dispersionless (Einstein)…

Strongly Correlated Electrons · Physics 2015-05-19 Christopher J. Pearson , William Barford , Robert J. Bursill

Using Bogoliubov theory we calculate the excitation spectrum of a spinor Bose-Einstein condensed gas with equal Rashba and Dresselhaus spin-orbit coupling in the stripe phase. The emergence of a double gapless band structure is pointed out…

Quantum Gases · Physics 2013-06-11 Yun Li , Giovanni I. Martone , Lev P. Pitaevskii , Sandro Stringari

We identify a new universality class of phase transitions that emerges in non-normal systems, extending the classical framework beyond eigenvalue instabilities. Unlike traditional critical phenomena, where transitions occur when eigenvalues…

Statistical Mechanics · Physics 2025-09-15 Virgile Troude , Didier Sornette

We consider the estimation of a sparse parameter vector from measurements corrupted by white Gaussian noise. Our focus is on unbiased estimation as a setting under which the difficulty of the problem can be quantified analytically. We show…

Information Theory · Computer Science 2010-02-02 Alexander Jung , Zvika Ben-Haim , Franz Hlawatsch , Yonina C. Eldar

Glasses are structurally disordered solids that host, in addition to crystalline-like phonons, vibrational excitations with no direct phononic counterpart. A long-standing universal signature is the excess vibrational density of…

Soft Condensed Matter · Physics 2026-01-28 Hideyuki Mizuno , Emi Minamitani

The density matrix renormalization group method is used to investigate the Peierls transition for the extended Hubbard model coupled to quantized phonons. Following our earlier work on spin-Peierls systems, we use a phonon spectrum that…

Strongly Correlated Electrons · Physics 2015-05-20 Christopher J. Pearson , William Barford , Robert J. Bursill

Bilinear inverse problems (BIPs), the resolution of two vectors given their image under a bilinear mapping, arise in many applications. Without further constraints, BIPs are usually ill-posed. In practice, properties of natural signals are…

Information Theory · Computer Science 2015-01-27 Yanjun Li , Kiryung Lee , Yoram Bresler

The paper analyzes four classical signal-plus-noise models: the factor model, spiked sample covariance matrices, the sum of a Wigner matrix and a low-rank perturbation, and canonical correlation analysis with low-rank dependencies. The…

Methodology · Statistics 2026-02-04 Anna Bykhovskaya , Vadim Gorin , Sasha Sodin

We consider a class of sparse random matrices, which includes the adjacency matrix of Erd\H{o}s-R\'enyi graphs $\mathcal G(N,p)$ for $p \in [N^{\varepsilon-1},N^{-\varepsilon}]$. We identify the joint limiting distributions of the…

Probability · Mathematics 2020-03-13 Yukun He

Among the many ways to model signals, a recent approach that draws considerable attention is sparse representation modeling. In this model, the signal is assumed to be generated as a random linear combination of a few atoms from a…

Computer Vision and Pattern Recognition · Computer Science 2015-05-18 Javier Turek , Irad Yavneh , Matan Protter , Michael Elad

A waveform channel is considered where the transmitted signal is corrupted by Wiener phase noise and additive white Gaussian noise. A discrete-time channel model that takes into account the effect of filtering on the phase noise is…

Information Theory · Computer Science 2017-08-15 Hassan Ghozlan , Gerhard Kramer

A waveform channel is considered where the transmitted signal is corrupted by Wiener phase noise and additive white Gaussian noise (AWGN). A discrete-time channel model is introduced that is based on a multi-sample receiver. Tight lower…

Information Theory · Computer Science 2013-03-28 Hassan Ghozlan , Gerhard Kramer

The increasing sensitivity of gravitational-wave detectors has brought about an increase in the rate of astrophysical signal detections as well as the rate of "glitches"; transient and non-Gaussian detector noise. Temporal overlap of…

General Relativity and Quantum Cosmology · Physics 2022-08-18 Sophie Hourihane , Katerina Chatziioannou , Marcella Wijngaarden , Derek Davis , Tyson Littenberg , Neil Cornish