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Structural health monitoring (SHM) relies on non-destructive techniques such as acoustic emission (AE) that generate large amounts of data over the lifespan of systems. Clustering methods are used to interpret these data and gain insights…

We propose fully data-driven variational methods, termed successive jump and mode decomposition (SJMD) and its multivariate extension, successive multivariate jump and mode decomposition (SMJMD), for successively decomposing nonstationary…

Signal Processing · Electrical Eng. & Systems 2025-04-24 Mojtaba Nazari , Anders Rosendal Korshøj , Naveed ur Rehman

Clustering based on vibration responses, such as transmissibility functions (TFs), is promising in structural anomaly detection. However, most existing methods struggle to determine the optimal cluster number, handle high-dimensional…

Machine Learning · Computer Science 2025-10-21 Lin-Feng Mei , Wang-Ji Yan

The kernel support vector machine (SVM) is one of the most widely used classification methods; however, the amount of computation required becomes the bottleneck when facing millions of samples. In this paper, we propose and analyze a novel…

Machine Learning · Computer Science 2013-11-06 Cho-Jui Hsieh , Si Si , Inderjit S. Dhillon

Efficient exact algorithms for Discrete Optimization (DO) rely heavily on strong primal and dual bounds. Relaxed Decision Diagrams (DDs) provide a versatile mechanism for deriving such dual bounds by compactly over-approximating the…

Artificial Intelligence · Computer Science 2025-12-18 Mohsen Nafar , Michael Römer , Lin Xie

This work introduces a new unsupervised representation learning technique called Deep Convolutional Transform Learning (DCTL). By stacking convolutional transforms, our approach is able to learn a set of independent kernels at different…

Machine Learning · Computer Science 2020-10-05 Jyoti Maggu , Angshul Majumdar , Emilie Chouzenoux , Giovanni Chierchia

In this paper, two kinds of high-order compact finite difference schemes for second-order derivative are developed. Then a second-order numerical scheme for Riemann-Liouvile derivative is established based on fractional center difference…

Numerical Analysis · Mathematics 2016-11-22 Hengfei Ding , Changpin Li

We investigate the mass spectrum and electromagnetic processes of charmonium system with the nonperturbative treatment for the spin-dependent potentials, comparing the pure scalar and scalar-vector mixing linear confining potentials. It is…

High Energy Physics - Phenomenology · Physics 2012-10-16 Lu Cao , You-Chang Yang , Hong Chen

This paper studies the bond valence method (BVM) and its application in the non-isovalent semiconductor alloy (GaN)$_{\rm{1-x}}$(ZnO)$_{\rm{x}}$. Particular attention is paid to the role of short-range order (SRO). A physical interpretation…

Materials Science · Physics 2016-10-14 Jian Liu

It is a common problem in lattice QCD calculation of the mass of the hadron with an annihilation channel that the signal falls off in time while the noise remains constant. In addition, the disconnected insertion calculation of the…

High Energy Physics - Lattice · Physics 2018-07-12 Keh-Fei Liu , Jian Liang , Yi-Bo Yang

Automatic differentiation is a tool for numerically calculating derivatives of a given function up to machine precision. This tool is useful for quantum chemistry methods, which require the calculation of gradients either for the…

Chemical Physics · Physics 2020-11-25 Fabijan Pavošević , Sharon Hammes-Schiffer

Recently developed pair coupled cluster doubles (pCCD) theory successfully reproduces doubly occupied configuration interaction (DOCI) with mean field cost. However, the projective nature of pCCD makes the method non-variational and thus…

Chemical Physics · Physics 2016-08-19 Luning Zhao , Eric Neuscamman

We present a modified Lanczos algorithm to diagonalize lattice Hamiltonians with dramatically reduced memory requirements, {\em without restricting to variational ansatzes}. The lattice of size $N$ is partitioned into two subclusters. At…

Strongly Correlated Electrons · Physics 2011-11-11 Marvin Weinstein , Assa Auerbach , V. Ravi Chandra

This paper describes a gradient-descent based optimization algorithm for synthesizing Constant Envelope Orthogonal Frequency Division Multiplexing (CE-OFDM) waveforms with low Auto-Correlation Function (ACF) sidelobes in a specified region…

Signal Processing · Electrical Eng. & Systems 2023-03-20 David G. Felton , David A. Hague

Cluster variation method (CVM) and path probability method (PPM) have generally been employed to study replacive phase transitions in alloy systems. Recently, displacive phase transitions have been explored within the realm of replacive…

Materials Science · Physics 2019-07-24 Ryo Yamada , Tetsuo Mohri

We extend a previous analysis [PRL {\bf 80}, 4693 (1998)] of breakdown of dynamical scale invariance in the coarsening of two-dimensional DLAs (diffusion-limited aggregates) as described by the Cahn-Hilliard equation. Existence of a second…

Disordered Systems and Neural Networks · Physics 2007-05-23 Massimo Conti , Baruch Meerson , Pavel V. Sasorov

We study decoherence processes of an S = 1/2 localized spin coupled to conduction band electrons in a metal or a semiconductor via an Ising-like interaction. We derive master equations for the density matrix of the localized spin, by…

Materials Science · Physics 2009-11-13 Naoyoshi Yamada , Akimasa Sakuma , Hiroki Tsuchiura

The dynamical cluster-decay model (DCM) is developed further for the decay of hot and rotating compound nuclei (CN) formed in light heavy-ion reactions. The model is worked out in terms of only one parameter, namely the neck-length…

Nuclear Experiment · Physics 2008-11-26 Raj K. Gupta , M. Balasubramaniam , Rajesh Kumar , Dalip Singh , C. Beck , W. Greiner

The coupled cluster method (CCM) is a method of quantum many-body theory that may provide accurate results for the ground-state properties of lattice quantum spin systems even in the presence of strong frustration and for lattices of…

Strongly Correlated Electrons · Physics 2009-11-11 D. J. J. Farnell , J. Schulenburg , J. Richter , K. A. Gernoth

A general method is described for detecting and analysing galaxy systems. The multivariate geometrical structure of the sample is studied by using an extension of the method which we introduced in a previous paper. The method is based on an…

Astrophysics · Physics 2015-06-24 Armando Pisani