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A tree decomposition of the coordinates of a code is a mapping from the coordinate set to the set of vertices of a tree. A tree decomposition can be extended to a tree realization, i.e., a cycle-free realization of the code on the…

Information Theory · Computer Science 2016-11-17 Navin Kashyap

In this work, we study two types of constraints on two-dimensional binary arrays. In particular, given $p,\epsilon>0$, we study (i) The $p$-bounded constraint: a binary vector of size $m$ is said to be $p$-bounded if its weight is at most…

Information Theory · Computer Science 2022-08-22 Tuan Thanh Nguyen , Kui Cai , Han Mao Kiah , Kees A. Schouhamer Immink , Yeow Meng Chee

In this paper we study the structure of solutions of the one dimensional weighted total variation regularisation problem, motivated by its application in signal recovery tasks. We study in depth the relationship between the weight function…

Optimization and Control · Mathematics 2016-09-06 Michael Hintermüller , Konstantinos Papafitsoros , Carlos N. Rautenberg

In this paper, we propose a novel design of image deblurring in the form of one-shot convolution filtering that can directly convolve with naturally blurred images for restoration. The problem of optical blurring is a common disadvantage to…

Image and Video Processing · Electrical Eng. & Systems 2019-07-22 Mahdi S. Hosseini , Konstantinos N. Plataniotis

We consider linear inverse problems in a nonparametric statistical framework. Both the signal and the operator are unknown and subject to error measurements. We establish minimax rates of convergence under squared error loss when the…

Statistics Theory · Mathematics 2012-04-16 S. Delattre , M. Hoffmann , D. Picard , T. Vareschi

In this paper, we consider the use of Total Variation (TV) minimization for compressive imaging; that is, image reconstruction from subsampled measurements. Focusing on two important imaging modalities -- namely, Fourier imaging and…

Information Theory · Computer Science 2020-09-21 Ben Adcock , Nick Dexter , Qinghong Xu

This paper concerns solving the sparse deconvolution and demixing problem using $\ell_{1,2}$-minimization. We show that under a certain structured random model, robust and stable recovery is possible. The results extend results of Ling and…

Statistics Theory · Mathematics 2017-05-11 Axel Flinth

We present a method for supervised learning of sparsity-promoting regularizers, a key ingredient in many modern signal reconstruction problems. The parameters of the regularizer are learned to minimize the mean squared error of…

Machine Learning · Computer Science 2021-11-23 Avrajit Ghosh , Michael T. Mccann , Saiprasad Ravishankar

In this paper, we tackle the problem of blind image super-resolution(SR) with a reformulated degradation model and two novel modules. Following the common practices of blind SR, our method proposes to improve both the kernel estimation as…

Image and Video Processing · Electrical Eng. & Systems 2022-03-28 Ziwei Luo , Haibin Huang , Lei Yu , Youwei Li , Haoqiang Fan , Shuaicheng Liu

Non-uniform blind deblurring for general dynamic scenes is a challenging computer vision problem as blurs arise not only from multiple object motions but also from camera shake, scene depth variation. To remove these complicated motion…

Computer Vision and Pattern Recognition · Computer Science 2018-05-08 Seungjun Nah , Tae Hyun Kim , Kyoung Mu Lee

In this paper we study distributed storage systems with exact repair. We give a construction for regenerating codes between the minimum storage regenerating (MSR) and the minimum bandwidth regenerating (MBR) points and show that in the case…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-04-08 Toni Ernvall

We consider a variational model for periodic partitions of the upper half-space into three regions, where two of them have prescribed volume and are subject to the geometrical constraint that their union is the subgraph of a function, whose…

Analysis of PDEs · Mathematics 2022-10-19 Marco Bonacini , Riccardo Cristoferi

Emerging applications in manufacturing, wireless communication, and molecular data storage require robust coding schemes that remain effective under physical distortions where codewords may be arbitrarily fragmented and partially missing.…

Information Theory · Computer Science 2026-01-22 Canran Wang , Minghui Liwang , Netanel Raviv

Reconstructing continuous signals from a small number of discrete samples is a fundamental problem across science and engineering. In practice, we are often interested in signals with 'simple' Fourier structure, such as bandlimited,…

Data Structures and Algorithms · Computer Science 2018-12-24 Haim Avron , Michael Kapralov , Cameron Musco , Christopher Musco , Ameya Velingker , Amir Zandieh

Information about microscopic objects with features smaller than the diffraction limit is almost entirely lost in a far-field diffraction image but could be partly recovered with data completition techniques. Any such approach critically…

Optics · Physics 2020-11-17 Maria Bancerek , Krzysztof M. Czajkowski , Rafal Kotynski

A scheme to reduce translational noninvariant quasi-one-dimensional wave guides into singly or multiply connected one-dimensional (1D) lines is proposed. It is meant to simplify the analysis of wave guides, with the low-energy properties of…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 Khee-Kyun Voo

This paper considers the problem of recovering a one or two dimensional discrete signal which is approximately sparse in its discrete gradient from an incomplete subset of its discrete Fourier coefficients which have been corrupted with…

Numerical Analysis · Mathematics 2015-06-10 Clarice Poon

The minimum distance graph of a code has the codewords as vertices and edges exactly when the Hamming distance between two codewords equals the minimum distance of the code. A constructive proof for reconstructibility of an extended perfect…

Information Theory · Computer Science 2009-05-31 Ivan Yu. Mogilnykh , Patric R. J. Östergård , Olli Pottonen , Faina I. Solov'eva

This article describes a probabilistic formulation of a Weighted Power minimization Distortionless response convolutional beamformer (WPD). The WPD unifies a weighted prediction error based dereverberation method (WPE) and a minimum power…

Audio and Speech Processing · Electrical Eng. & Systems 2019-08-08 Tomohiro Nakatani , Keisuke Kinoshita

We consider whether minimizers for total variation regularization of linear inverse problems belong to $L^\infty$ even if the measured data does not. We present a simple proof of boundedness of the minimizer for fixed regularization…

Optimization and Control · Mathematics 2023-06-28 Kristian Bredies , José A. Iglesias , Gwenael Mercier