The problem of the integral representation over a bounded surface of a regular field satisfying the Helmholtz equation in all space is investigated. This problem is equivalent to local splitting into an incoming field and an outgoing field. This spli...
We implement the Direction-Splitting solver originally proposed by Keating and Minev in 2013 and allow complex geometries to be described by a triangulation defined in STL files. We develop an algorithm that computes intersections and distances betwe...
When performing fractional factorial experiments in a completely random order is impractical, fractional factorial split-plot designs are suitable options as an alternative. It is well recognized that the more there are lower order effects of interes...
The purpose of this paper is to propose an iterative algorithm for solving the split equality common null point problem (SECNP), which is to find an element of the set of common zero points for a finite family of maximal monotone operators in Hilbert...
We present a total-variation-regularized image segmentation model that uses local regularization parameters to take into account spatial image information. We propose some techniques for defining those parameters, based on the cartoon-texture decompo...
In this paper, we studied variational inequalities and fixed point problems in nonconvex cases. By the projection method over prox-regularity sets, the convergence of the suggested iterative scheme was established under some mild rules.
Marine seismic imaging is affected by limited acquisition aperture, nonuniform illumination, and complex features such as seafloor structures and low-velocity gas clouds. These factors can produce blurred reflectors, amplitude imbalance, and migratio...
We study the solvability of the Ionkin problem for some differential equations with one space variable. These equations include parabolic and quasiparabolic, hyperbolic and quasihyperbolic, pseudoparabolic and pseudohyperbolic, elliptic and quasielli...
Noise in an image can affect one’s extraction of image information, therefore, image denoising is an important image pre-processing process. Many of the existing models have a large number of estimated parameters, which increases the time compl...
Unsupervised learning often relies on non-negative matrix factorization (NMF) for extracting low-dimensional features. Standard deep NMF models, however, tend to miss complex hierarchical patterns and may warp the intrinsic geometry of high-dimension...
In this paper, we propose the simultaneous sub-gradient projection algorithm with the dynamic step size (SSPA for short) for solving the multiple-sets split feasibility problem (MSSFP for short) and investigate its linear convergence. We involve a no...
This review surveys the mathematical theory and methods of state estimation for stochastic dynamical systems when the Gaussian-linear-least-squares paradigm fails, focusing on the role of sparsity-promoting and constraint-encoding regularization. The...
Residential air conditioning systems are a major contributor to household electricity consumption in tropical regions, where environmental factors such as climate variability and particulate pollution (PM10) can further increase cooling demand and ac...
This paper investigates a nonlinear inverse problem in a time fractional diffusion-wave equation, in which a spatially varying potential coefficient is recovered from noisy final-time measurements. A local uniqueness result for the inverse problem is...
The present study utilized response surface methodology (RSM) and Bayesian neural network (BNN) to predict the characteristics of a diesel engine powered by a blend of biodiesel and diesel fuel. The biodiesel was produced from waste cooking oil using...
In this paper, SAR image reconstruction with joint phase error estimation (autofocusing) is formulated as an inverse problem. An optimization model utilising a sparsity-enforcing Cauchy regularizer is proposed, and an alternating minimization framewo...
Persistence, coexistence, competitive exclusion, and global asymptotic stability (GAS) are closely related problems in mathematical epidemiology that are often treated by model-specific arguments. We develop a unified approach to GAS based on Perron&...
Motivation: We aim to study the boundary stability and persistence of positive odes in mathematical epidemiology models by importing structural tools from chemical reaction networks. This is largely a review work, which attempts to congregate the fie...
Persistence, coexistence, and boundary transcritical relays are usually studied through model-specific analyses in mathematical epidemiology, ecology, population dynamics, and chemical reaction network theory. Although these fields address closely re...
In super-low-frequency (SLF) submarine communication, the motion-induced noise of the towed antenna is the primary noise source, and below 500 Hz, it increases with increasing speed. We propose an improved quadratic Approximate Forward–Backward...
This paper presents a partially symmetric regularized two-step inertial alternating direction method of multipliers for solving non-convex split feasibility problems (SFP), which adds a two-step inertial effect to each subproblem and includes an inte...
Anatomical malformations, obliterations of the cochlea, or re-implantations pose particular challenges in cochlear implantation. Treatment methods rely on radiological and intraoperative findings and include incomplete insertion, the implantation of...
The proximal split feasibility problem is investigated in Hilbert spaces. An iterative procedure is introduced for finding the solution of the proximal split feasibility problem. Strong convergence analysis of the presented algorithm is proved.
We study three classes of variational inclusion problems in the framework of a real Hilbert space and propose a simple modification of Tseng’s forward-backward-forward splitting method for solving such problems. Our algorithm is obtained via a...
The regularization method has a direct impact on the accuracy of the reconstructed sound field in the process of inverse calculation of near−field acoustic holography using the equivalent source method. To expand the frequency range of sound fi...
In this paper, we consider a two-dimensional acoustic wave equation in an unbounded domain and introduce a modified model of the classical un-split perfectly matched layer (PML). We apply a regularization technique to a lower order regularity term em...
Deconvolution methods can be used to improve the azimuth resolution in airborne radar imaging. Due to the sparsity of targets in airborne radar imaging, an
Reliable prediction of monopile self-weight penetration depth is essential for drivability assessment and installation planning but remains challenging because of nonlinear pile–soil interaction and limited field data. This study compiles recor...
In order to overcome the spectral interference of the conventional Fourier transform in the International Electrotechnical Commission framework, this paper introduces a Bregman-split-based compressive sensing (BSCS) method to estimate the Taylor&ndas...
One of the significant features of extreme learning machines (ELMs) is their fast convergence. However, in the big data environment, the ELM based on the Moore–Penrose matrix inverse still suffers from excessive calculation loads. Leveraging th...
This paper proposes a new group-sparsity-inducing regularizer to approximate
Blind image deblurring, which requires simultaneous estimation of the latent image and blur kernel, constitutes a classic ill-posed problem. To address this, priors based on
25 November 2020
Regarding the sharp growth rate of ICT (information and communication technology)—based mobility services like ridesourcing, it is essential to investigate the impact of these new mobility services on the transport mode choices, particularly on...
This work focuses on the problem of rain removal from a single image. The directional multilevel system, Shearlets, is used to describe the intrinsic directional and structure sparse priors of rain streaks and the background layer. In this paper, a S...
This paper presents a novel pentagonal structure dual-core photonic crystal fiber polarizing beam splitter (PS-DC-PCF PBS) filled with a nematic liquid crystal (NLC) in the central hole. Unlike previous designs with symmetric arrangements, the upper...
Bilayer ion-exchange membranes are mainly used for separating single and multiply charged ions. It is well known that in membranes in which the layers have different charges of the ionogenic groups of the matrix, the limiting current decreases, and t...
The Split Bregman method (SBM), a popular and universal CS reconstruction algorithm for inverse problems with both l1-norm and TV-norm regularization, has been extensively applied in complex domains through the complex-to-real transforming technique,...
Superhydrophobic surface is regarded as important topic in the field of thermal fluids today due to its unique features on flow drag reduction and heat transfer enhancement. In this study, the pseudo-cavitation phenomenon on the superhydrophobic surf...
Total variation (TV) regularization has received much attention in image restoration applications because of its advantages in denoising and preserving details. A common approach to address TV-based image restoration is to design a specific algorithm...
The sparse iterative covariance-based estimation (SPICE) method has recently gained significant attraction in the field of scanning radar super-resolution imaging because of its angular resolution enhancement capability. However, it is unable to pres...
The main purpose of this paper is to study the Cauchy problem of sixth order viscous Cahn–Hilliard equation with Willmore regularization. Because of the existence of the nonlinear Willmore regularization and complex structures, it is difficult...
This research introduces three novel zeroing neural network (ZNN) models for addressing the time-varying Yang–Baxter-like matrix equation (TV-YBLME) with arbitrary (regular or singular) real time-varying (TV) input matrices in continuous time....
We determined whether improvements in metabolic health occur when sedentary office workers replace their regular workplace lunches with pulse-based meals (containing chickpeas, lentils, or split peas). We first tested 10 meals for favourability in 18...
Federated learning (FL) struggles under non-IID client data when local models drift toward conflicting optima, impairing global convergence and performance. We introduce entropy-regularized federated optimization (ERFO), a lightweight client-side mod...
Aimed at the issue of estimating the fault component from a noisy observation, a novel detection approach based on augmented Huber non-convex penalty regularization (AHNPR) is proposed. The core objectives of the proposed method are that (1) it estim...
It is a primary challenge in the fault diagnosis community of the gearbox to extract the weak fault features under heavy background noise and nonstationary conditions. For this purpose, a novel weak fault detection approach based on majorization&ndas...
Sparse signal processing has been used in synthetic aperture radar (SAR) imaging due to the maturity of compressed sensing theory. As a typical sparse reconstruction method,
Identifying the small group of customers who hold a given policy in severely imbalanced tabular data is a recurring screening problem in insurance analytics. This study considers binary caravan-insurance policy-ownership classification on the COIL 20...
In this article, based on the regularization techniques, we construct two new algorithms combining the forward-backward splitting algorithm and the proximal contraction algorithm, respectively. Iterative sequences of the new algorithms can converge s...
Digital soil mapping has become increasingly important for large-scale soil organic carbon (SOC) assessments, yet the choice of accuracy assessment method significantly influences model performance interpretation. This study investigates the impact o...
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