3,988 Results Found

This paper presents a new l₁-RLS method to estimate a sparse impulse response estimation. A new regularization factor calculation method is proposed for l₁-RLS that requires no information of the true channel response in advance. In addition, we also...

In this paper, we propose a new calculation method for the regularization factor in sparse recursive least squares (SRLS) with $l_1$-norm penalty. The proposed regularization factor requires no prior knowledge of the actual system impulse response, and...

The online sequential extreme learning machine with persistent regularization and forgetting factor (OSELM-PRFF) can avoid potential singularities or ill-posed problems of online sequential regularized extreme learning machines with forgetting factor...

Hyperspectral image (HSI) super-resolution is a vital technique that generates high spatial-resolution HSI (HR-HSI) by integrating information from low spatial-resolution HSI with high spatial-resolution multispectral image (MSI). However, existing s...

A technical challenge for workload prediction in microservice systems is how to capture both the dynamic features of workload and evolving dependencies among microservices. The existing work focused mainly on modeling dynamic features without taking...

We study two-tone factors in edge-connected regular graphs and claw-free cubic graphs under red-blue vertex colorings. A two-tone factor is a spanning subgraph in which vertices of different colors are assigned different allowed degree sets. For edge...

Graph regularized non-negative matrix factorization (GNMF) is widely used in feature extraction. In the process of dimensionality reduction, GNMF can retain the internal manifold structure of data by adding a regularizer to non-negative matrix factor...

Nonnegative matrix factorization (NMF) has been shown to be a strong data representation technique, with applications in text mining, pattern recognition, image processing, clustering and other fields. In this paper, we propose a hypergraph-regulariz...

An objective existence of damped oscillation regular structures from the proton “effective” electromagnetic form factor data, appearing when these data are described by a two parametric Tomasi-Gustafsson-Rekalo function, is investigated....

Matrix factorization based methods have widely been used in data representation. Among them, Non-negative Matrix Factorization (NMF) is a promising technique owing to its psychological and physiological interpretation of spontaneously occurring data....

NONNEGATIVE matrix factorization (NMF) is an effective technique for dimensionality reduction of high-dimensional data for tasks such as machine learning and data visualization. However, for practical clustering tasks, traditional NMF ignores the man...

Clustering plays a crucial role in data mining and knowledge discovery, where non-negative matrix factorization (NMF) has attracted widespread attention due to its effective data representation and dimensionality reduction capabilities. However, stan...

Traditional non-negative matrix factorization (NMF) faces challenges when dealing with complex data, primarily characterized by sensitivity to noise, neglect of data geometric structure, and inability to effectively utilize supervised information. To...

Value factorization methods have become a standard tool for cooperative multi-agent reinforcement learning (MARL) in the centralized-training, decentralized-execution (CTDE) setting. QMIX (a monotonic mixing network for value factorization), in parti...

Non-negative matrix factorization (NMF) is widely used as a powerful matrix factorization tool in data representation. However, the traditional NMF, measured by Euclidean distance or Kullback–Leibler distance, does not take into account the int...

Multi-label classification has been extensively researched and utilized for several decades. However, the performance of these methods is highly susceptible to the presence of noisy data samples, resulting in a significant decrease in accuracy when n...

Hyperspectral image (HSI) change detection (CD) is an important technology for identifying surface changes using multi-temporal HSIs. Nevertheless, the high dimensionality of HSIs presents significant challenges for CD tasks, including issues such as...

Underwater passive acoustic monitoring (PAM) serves as a core approach pervasively applied to the long-term, non-invasive detection of biological acoustic signals. Dolphin whistles serve as a fundamental aspect of vocal communication, exhibiting intr...

The objective of this study was to investigate the prevalence of regular physical activity (RPA) among middle-aged and older adults in urban communities in Jinan, China, and to identify the factors related to RPA. A cross-sectional survey was conduct...

Advances in information technology have harnessed the application of Quick Response (QR) codes in day-to-day activities, simplifying information exchange. QR codes are witnessed almost everywhere, on consumables, newspapers, information bulletins, et...

Concrete tensile properties usually govern the fatigue cracking of structural components such as bridge decks under repetitive loading. A fatigue life reliability analysis of commonly used ordinary cement concrete is desirable. As fatigue is affected...

Non-negative Matrix Factorization (NMF) has gained popularity due to its effectiveness in clustering and feature selection tasks. It is particularly valuable for managing high-dimensional data by reducing dimensionality and providing meaningful seman...

Due to the advantages of high convergence accuracy, fast training speed, and good generalization performance, the extreme learning machine is widely used in model identification. However, a gas turbine is a complex nonlinear system, and its sampling...

A hyperspectral image (HSI) is often corrupted by various types of noise during image acquisition, e.g., Gaussian noise, impulse noise, stripes, deadlines, and more. Thus, as a preprocessing step, HSI denoising plays a vital role in many subsequent t...

Error in the method of regularized Stokeslets is highly dependent on the choice of the blob or regularization function that is utilized to handle singularities in the flow. In this work, we develop a general framework to choose regularizations at the...

In this paper, we present an explicit formula for the approximate solution of the Cauchy problem for the matrix factorizations of the Helmholtz equation in a bounded domain on the plane. Our formula for an approximate solution also includes the const...

In 2005, Shi defined I-regular S-posets and used this concept to characterize $PP$-pomonoids and po-cancellable pomonoids. In this paper, we continued the development of the homological classification of pomonoids by using the I-regularity of S-posets....

Magnetotellurics (MT) is an important geophysical method for resource exploration and mineral evaluation. As a direct and effective form of data interpretation, MT inversion is usually considered to be a penalty-function constraint-based optimization...

Gambling participation among women and older adults has increased, yet research on the psychosocial determinants of gambling in these groups remains limited. This study explored sex- and age-related differences in gambling frequency, the influence of...

The problem of predicting students’ performance has been recently tackled by using matrix factorization, a popular method applied for collaborative filtering based recommender systems. This problem consists of predicting the unknown performance...

In this paper, we define and study the concept of the factorizable semihypergroup, i.e., a semihypergroup that can be written as a hyperproduct of two proper sub-semihypergroups. We consider some classes of semihypergroups such as regular semihypergr...

Factor analysis is one of the most important statistical tools for analyzing multivariate data (i.e., items) in the social sciences. An essential case is the comparison of multiple groups on a one-dimensional factor variable that can be interpreted a...

In this paper, using the construction of the Carleman matrix, we explicitly find a regularized solution of the Cauchy problem for matrix factorizations of the Helmholtz equation in a three-dimensional unbounded domain.

In this paper, we present a novel unsupervised feature selection method termed robust matrix factorization with robust adaptive structure learning (RMFRASL), which can select discriminative features from a large amount of multimedia data to improve t...

Recently, community detection has emerged as a prominent research area in the analysis of complex network structures. Community detection models based on non-negative matrix factorization (NMF) are shallow and fail to fully discover the internal stru...

Single-cell RNA sequencing (scRNA-seq) provides a high-resolution view of cellular heterogeneity, yet accurate cell-type annotation remains challenging due to data sparsity, technical noise, and variability across tissues, platforms, and species. Man...

Community structure is a significant characteristic of complex networks, and community detection has valuable applications in network structure analysis. Non-negative matrix factorization (NMF) is a key set of algorithms used to solve the community d...

Regular maintenance of non-communicable chronic diseases can constrain disease progression in diabetic and hypertensive patients. To identify the individual and social factors that are associated with positive health-seeking behaviors and regular mai...

The viscoelastic relaxation spectrum is vital for constitutive models and for insight into the mechanical properties of materials, since, from the relaxation spectrum, other material functions used to describe rheological properties can be uniquely d...

The classification of wireless communication channel scenarios is vital for modern wireless technologies. Efficient data preprocessing for identification, especially starting from 5G and beyond, where multiple scenario transitions occur, is crucial....

The paper describes an application of the p-regularity theory to Quadratic Programming (QP) and nonlinear equations with quadratic mappings. In the first part of the paper, a special structure of the nonlinear equation and a construction of the 2-fac...

Cancer genomic data contain views from different sources that provide complementary information about genetic activity. This provides a new way for cancer research. Feature selection and multi-view clustering are hot topics in bioinformatics, and the...

In this paper, we proposed a logistic regression model with $l_{p,q}$ regularization that could give a group sparse solution. The model could be applied to variable-selection problems with sparse group structures. In the context of big data, the solutions...

The suboptimal procedure under consideration, based on the MDR-EFE algorithm, provides sequential selection of relevant (in a sense) factors affecting the studied, in general, non-binary random response. The model is not assumed linear, the joint dis...

Let $G=(V,E)$ be a finite simple graph with $p=\left|V\right|$ vertices and $q=\left|E\right|$ edges, without isolated vertices or isolated edges. A vertex magic total labeling is a bijection f from $V\cup E$ to the consecutive integers $1,2,\dots ,p+q,$ with the property that, f...

Nonnegative matrix factorization (NMF) is an efficient method for feature learning in the field of machine learning and data mining. To investigate the nonlinear characteristics of datasets, kernel-method-based NMF (KNMF) and its graph-regularized ex...

In the present paper, we introduce the concept of idempotent-aided factorization (I.-A. factorization) of a regular element of a semigroup, which can be understood as a semigroup-theoretical extension of full-rank factorization of matrices over a fie...

In seismic refraction exploration, travel time tomography is the most widely used method in engineering and environmental geophysical exploration. In this paper, we mainly optimize the travel time tomography of refraction. First, with respect to the...

Battery state of charge prediction is one of the most essential state quantities of a battery management system. It is a prerequisite for the operation of a battery management system, but it becomes difficult to make an exact prediction of its state...

A rigorous approach was employed for the accurate evaluation of the electromagnetic interaction between a thin metallic rod and a two-dimensional (2D) slotted cavity. The problem was posed as a classical boundary value problem for the Helmholtz equat...