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The functional linear model extends the notion of linear regression to the case where the response and covariates are iid elements of an infinite dimensional Hilbert space. The unknown to be estimated is a Hilbert-Schmidt operator, whose…

Statistics Theory · Mathematics 2016-12-22 Tung Pham , Victor Panaretos

In this work, a new class of vector-valued phase field models is presented, where the values of the phase parameters are constrained by a convex set. The generated phase fields feature the partition of the domain into patches of distinct…

Analysis of PDEs · Mathematics 2023-11-03 Orestis Vantzos

Frames in a separable quaternionic Hilbert space were introduced and studied in [17] to have more applications. In this paper, we extend the study of frames in quaternionic Hilbert spaces and introduce different types of duals of a frame in…

Functional Analysis · Mathematics 2018-03-16 S. K. Sharma , Ghanshyam Singh , Soniya Sahu

We propose a flexible convex relaxation for the phase retrieval problem that operates in the natural domain of the signal. Therefore, we avoid the prohibitive computational cost associated with "lifting" and semidefinite programming (SDP)…

Information Theory · Computer Science 2017-03-17 Sohail Bahmani , Justin Romberg

Several strategies in phase retrieval are unified by an iterative "difference map" constructed from a pair of elementary projections and a single real parameter $\beta$. For the standard application in optics, where the two projections…

Numerical Analysis · Mathematics 2025-10-20 Veit Elser

The phase retrieval problem asks to recover a natural signal $y_0 \in \mathbb{R}^n$ from $m$ quadratic observations, where $m$ is to be minimized. As is common in many imaging problems, natural signals are considered sparse with respect to…

Information Theory · Computer Science 2018-07-12 Paul Hand , Oscar Leong , Vladislav Voroninski

Formal structure of phase-space path integrals based on different types of operator orderings is analysed.

Statistical Mechanics · Physics 2009-06-16 L. I. Plimak

This work studies phase retrieval for wave fields, aiming to recover the phase of an incoming wave from multi-plane intensity measurements behind different types of linear and nonlinear media. We show that unique phase retrieval can be…

Optics · Physics 2025-05-22 Yan Cheng , Kui Ren , Nathan Soedjak

Rhythmic activity is ubiquitous in biological systems from the cellular to organism level. Reconstructing the instantaneous phase is the first step in analyzing the essential mechanism leading to a synchronization state from the observed…

Adaptation and Self-Organizing Systems · Physics 2022-09-02 Akari Matsuki , Hiroshi Kori , Ryota Kobayashi

In this paper, we study the Hilbert$-$Schmidt frame (HS-frame) theory for separable Hilbert spaces. We first present some characterizations of HS-frames and prove that HS-frames share many important properties with frames. Then, we show how…

Functional Analysis · Mathematics 2017-06-26 Anirudha Poria

The phase retrieval problem in the classical setting is to reconstruct real/complex functions from the magnitudes of their Fourier/frame measurements. In this paper, we consider a new phase retrieval paradigm in the…

Functional Analysis · Mathematics 2019-09-06 Yang Chen , Cheng Cheng , Qiyu Sun

As a generalization of the standard phase retrieval problem, we seek to reconstruct symmetric rank-1 matrices from inner products with subclasses of positive semidefinite matrices. For such subclasses, we introduce random cubatures for…

Numerical Analysis · Mathematics 2017-09-04 Martin Ehler , Manuel Graef , Franz J. Kiraly

In this paper, we first introduce the notion of controlled weaving K-g-frames in Hilbert spaces. Then, we present sufficient conditions for controlled weaving K-g-frames in separable Hilbert spaces. Also, a characterization of controlled…

Functional Analysis · Mathematics 2018-12-04 Reza Rezapour , Asghar Rahimi , E. Osgooei , Hossien Dehghan

The reconstruction of phase spaces is an essential step to analyze time series according to Dynamical System concepts. A regression performed on such spaces unveils the relationships among system states from which we can derive their…

Machine Learning · Computer Science 2020-06-23 Lucas Pagliosa , Alexandru Telea , Rodrigo Mello

Iterative algorithms with feedback are amongst the most powerful and versatile optimization methods for phase retrieval. Among these, the hybrid input-output algorithm has demonstrated practical solutions to giga-element nonlinear phase…

Optics · Physics 2007-11-13 S. Marchesini

We construct frames adapted to a given cover of the time-frequency or time-scale plane. The main feature is that we allow for quite general and possibly irregular covers. The frame members are obtained by maximizing their concentration in…

Functional Analysis · Mathematics 2015-04-27 Monika Dörfler , José Luis Romero

Machine learning techniques have been shown to be effective to recognize different phases of matter and produce phase diagrams in the parameter space interested, while they usually require prior labeled data to perform well. Here, we…

In this paper, we develop a framework of generalized phase retrieval in which one aims to reconstruct a vector ${\mathbf x}$ in ${\mathbb R}^d$ or ${\mathbb C}^d$ through quadratic samples ${\mathbf x}^*A_1{\mathbf x}, \dots, {\mathbf…

Information Theory · Computer Science 2016-06-06 Yang Wang , Zhiqiang Xu

Controlled frames and g-frames were considered recently as generalizations of frames in Hilbert spaces. In this paper we generalize some of the known results in frame theory to controlled g-frames. We obtain some new properties of…

Functional Analysis · Mathematics 2019-12-19 Dongwei Li , Jinsong Leng

Most methods tackling the phase retrieval problem of magnitude-only antenna measurements suffer from unrealistic sampling requirements, from unfeasible computational complexities, and, most severely, from the lacking reliability of…

Signal Processing · Electrical Eng. & Systems 2022-02-01 Alexander Paulus , Josef Knapp , Jonas Kornprobst , Thomas F. Eibert
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