Results 41 to 50 of about 16,496,952 (144)

Quantum Algorithms for the Multiplication of Circulant Matrices and Vectors

open access: yesInformation
This article presents two quantum algorithms for computing the product of a circulant matrix and a vector. The arithmetic complexity of the first algorithm is O(Nlog2N) in most cases. For the second algorithm, when the entries in the circulant matrix and
Lu Hou, Zhenyu Huang, Chang Lv
doaj   +1 more source

Accelerating Conjugate Gradient Solvers for Homogenization Problems With Unitary Neural Operators

open access: yesInternational Journal for Numerical Methods in Engineering, Volume 127, Issue 5, 15 March 2026.
ABSTRACT Rapid and reliable solvers for parametric partial differential equations (PDEs) are needed in many scientific and engineering disciplines. For example, there is a growing demand for composites and architected materials with heterogeneous microstructures.
Julius Herb, Felix Fritzen
wiley   +1 more source

VanderLaan Circulant Type Matrices [PDF]

open access: yes, 2015
Circulant matrices have become a satisfactory tools in control methods for modern complex systems. In the paper, VanderLaan circulant type matrices are presented, which include VanderLaan circulant, left circulant, and g-circulant matrices.
Hongyan Pan, Zhaolin Jiang
core   +1 more source

POSITIVE SEMI-DEFINITENESS OF GENERALIZED ANTI-CIRCULANT TENSORS

open access: yes, 2016
Anti-circulant tensors have applications in exponential data fitting. They are special Hankel tensors. In this paper, we extend the definition of anti-circulant tensors to generalized anti-circulant tensors by introducing a circulant index r such that ...
Qun Wang   +5 more
core   +1 more source

On the Approximation of Precision Matrices for Wide-Swath Altimetry

open access: yesRemote Sensing
New observations of ocean surface topography obtained by wide-swath satellite interferometry require new capabilities to process spatially correlated errors in order to assimilate these data into numerical models.
Max Yaremchuk   +2 more
doaj   +1 more source

Definition and Computation of Tensor‐Based Generalized Function Composition

open access: yesNumerical Linear Algebra with Applications, Volume 33, Issue 1, February 2026.
ABSTRACT Functions are fundamental to mathematics as they offer a structured and analytical framework to express relations between variables. While scalar and matrix‐based functions are well‐established, higher‐order tensor‐based functions have not been as extensively explored.
Remy Boyer
wiley   +1 more source

The norm of a circulant operator [PDF]

open access: yes, 2022
In this talk, we’ll present our study of the induced p-norm of circulant matrices A(n, +/- a, b), acting as operators on the Euclidean space R^n. For circulant matrices whose entries are nonnegative real numbers, in particular for A(n, a, b), we provide ...
Bouthat, Ludovick   +2 more
core   +1 more source

Estimates of the p-norms of solutions and inverse matrices of systems of linear equations with a circulant matrix [PDF]

open access: yes
This article considers the problem of estimating solutions and inverse matrices of systems of linear equations with a circulant matrix in the matrix norms induced by the vector p-norm for 1 < p ...
Morneau-Guérin, Frédéric
core   +1 more source

Deep Reinforcement Learning‐Enabled QoS‐Aware Adaptive Modulation for Visible Light‐Infrared Communication Systems

open access: yesIET Communications, Volume 20, Issue 1, January/December 2026.
To address the challenges of channel sensitivity and reliability in aircraft cabin environments, this paper proposes a reinforcement learning‐assisted bidirectional communication system utilizing visible light for the downlink and infrared for the uplink. By combining an improved, resource‐efficient LMMSE algorithm for channel estimation with RL‐driven
Lei Xiao   +5 more
wiley   +1 more source

Range–Doppler Estimation With an EM‐Learned Prior for Pulse‐Agile Waveforms

open access: yesElectronics Letters, Volume 62, Issue 1, January/December 2026.
This letter proposes an expectation–maximisation (EM)‐based range–Doppler (RD) estimator that adaptively learns the clutter and target distributions and adjusts an RD prior map. By optimising the shrinkage strength via prior weighting, the proposed method improves RSM suppression in the region of interest.
Xiaojian Xu   +3 more
wiley   +1 more source

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