The main aim of this paper is to study quaternion matrix factorization for low-rank quaternion matrix completion and its applications in color image processing. For the real-world color images, we proposed a novel model called low-rank quaternion mat...
This paper studies the matrix completion problems when the entries are contaminated by non-Gaussian noise or outliers. The proposed approach employs a nonconvex loss function induced by the maximum correntropy criterion. With the help of this loss fu...
In this article we present and discuss a two step methodology to find the closest low rank completion of a sparse large matrix. Given a large sparse matrix M, the method consists of fixing the rank to r and then looking for the closest rank-r matrix...
Terrain classification is a hot topic in polarimetric synthetic aperture radar (PolSAR) image interpretation that aims at assigning a label to every pixel and forms a label matrix for a PolSAR image. From the perspective of human interpretation, clas...
The matrix completion problem aims to recover missing entries in a partially observed matrix by approximating it with a low-rank structure. The two common approaches—the singular value thresholding and matrix factorization with alternating leas...
In this paper, we study the problem of bilinear regression, a type of statistical modeling that deals with multiple variables and multiple responses. One of the main difficulties that arise in this problem is the presence of missing data in the respo...
Availability of reliable and extended datasets of recorded power output from renewables is nowadays seen as one of the key drivers to improve the design and control of smart energy systems. In particular, these datasets are needed to train artificial...
Protein phosphorylation is an important chemical modification catalyzed by kinases. It plays important roles in many cellular processes. Predicting kinase–substrate interactions is vital to understanding the mechanism of many diseases. Many com...
Real-time process data are the foundation for the successful implementation of intelligent manufacturing in the chemical industry. However, in the actual production process, process data may randomly be missing due to various reasons, thus affecting...
Low-rank matrix completion aims to recover an unknown matrix from a subset of observed entries. In this paper, we solve the problem via optimization of the matrix manifold. Specially, we apply QR factorization to retraction during optimization. We de...
Accurate node localization is essential for many Internet of Things (IoT) applications. However, incomplete and noisy distance measurements often degrade the reliability of the Euclidean Distance Matrix (EDM), which is critical for range-based locali...
Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of tho...
One of the main challenges faced by wireless sensor network (WSN) localization is the positioning accuracy of the WSN node. The existing algorithms are arduous to use for dealing with the pulse noise that is universal and ineluctable in practical con...
To improve the accuracy of color image completion with missing entries, we present a recovery method based on generalized higher-order scalars. We extend the traditional second-order matrix model to a more comprehensive higher-order matrix equivalent...
Large-scale symmetric arrays such as uniform linear arrays (ULA) have been widely used in wireless communications for improving spectrum efficiency and reliability. Channel state information (CSI) is critical for optimizing massive multiple-input mul...
In this paper, we study the two-dimensional direction of arrival (2D-DOA) estimation problem in a switching uniform circular array (SUCA), which means performing 2D-DOA estimation with a reduction in the number of radio frequency (RF) chains. We prop...
This paper focuses on two-dimensional (2-D) direction-of-arrival (DOA) estimation for an L-shaped array. While recent studies have explored sparse methods for this problem, most exploit only the cross-correlation matrix, neglecting self-correlation i...
In this paper, we propose a high accuracy fingerprint-based localization scheme for the Internet of Things (IoT). The proposed scheme employs mathematical concepts based on sparse representation and matrix completion theories. Specifically, the propo...
To obtain efficient data gathering methods for wireless sensor networks (WSNs), a novel graph based transform regularized (GBTR) matrix completion algorithm is proposed. The graph based transform sparsity of the sensed data is explored, which is also...
Resolution is the bottleneck for the application of radar imaging, which is limited by the bandwidth for the range dimension and synthetic aperture for the cross-range dimension. The demand for high azimuth resolution inevitably results in a large am...
In this paper, the two-dimensional (2-D) direction-of-arrival (DOA) estimation problem is explored for the sum-difference co-array (SDCA) generated by the virtual aperture expansion of co-prime planar arrays (CPPA). Since the SDCA has holes, this usu...
Many studies have clarified that microRNAs (miRNAs) are associated with many human diseases. Therefore, it is essential to predict potential miRNA-disease associations for disease pathogenesis and treatment. Numerous machine learning and deep learnin...
In this paper, we are interested in the data gathering for Wireless Sensor Networks (WSNs). In this context, we assume that only some nodes are active in the network, and that these nodes are not transmitting all the time. On the other side, the inac...
The integrity of real-time monitoring data is paramount to the accuracy of scientific research and the reliability of decision-making. However, data incompleteness arising from transmission interruptions or extreme weather disrupting equipment operat...
Exploring potential associations between small molecule drugs (SMs) and microRNAs (miRNAs) is significant for drug development and disease treatment. Since biological experiments are expensive and time-consuming, we propose a computational model base...
Sparse sensing schemes based on matrix completion for data collection have been proposed to reduce the power consumption of data-sensing and transmission in wireless sensor networks (WSNs). While extensive efforts have been made to improve the recove...
In estimating the two-dimensional (2D) direction-of-arrival (DOA) using a coprime planar array, the main issues are the high complexity of spectral peak search and the limited degree of freedom imposed by the number of sensors. In this paper, we pres...
With the rapid development of vibration and noise reduction technologies, underwater target detection is facing great challenges. Particularly, the task of high-resolution direction of arrival (DOA) estimation with sonar array is becoming more and mo...
In order to reduce power consumption and save storage capacity, we propose a high-resolution sub-Nyquist radar approach based on matrix completion (MC), termed as single-channel sub-Nyquist-MC radars. While providing the high-resolution joint angle-D...
This paper introduces an innovative rapid algorithm for estimating two-dimensional direction of arrival (2D-DOA) with randomly arranged electromagnetic vector sensor (EMVS) arrays under nonuniform noise conditions. The approach begins by forming the...
In the competitive landscape of online learning, developing robust and effective learning resource recommendation systems is paramount, yet the field faces challenges due to high-dimensional, sparse matrices and intricate user–resource interact...
A long-standing challenge for the structural health monitoring (SHM) community is the masking effect of environmental variability, typically addressed by orthogonal projection (OP)-based data normalization to isolate the influence of environmental va...
Millimeter-wave interferometric synthetic aperture radiometer (InSAR) can provide high-resolution observations for many applications by using small antennas to achieve very large synthetic aperture. However, reconstruction of a millimeter-wave InSAR...
In this paper, a new thresholding operator, namely, designed thresholding operator, is designed to recover the low-rank matrices. With the change of parameter in designed thresholding operator, the designed thresholding operator can apply less bias t...
Electromagnetic data annotation is one of the most important steps in many signal processing applications, e.g., radar signal deinterleaving and radar mode analysis. This work considers cooperative electromagnetic data annotation from multiple reconn...
This article is proposing a fast version of adaptive iterative matrix designed thresholding (AIMDT) algorithm which is studied in our previous work. In AIMDT algorithm, a designed thresholding operator is studied to the problem of recovering the low-...
The identification of potential microRNA (miRNA)-disease associations enables the elucidation of the pathogenesis of complex human diseases owing to the crucial role of miRNAs in various biologic processes and it yields insights into novel prognostic...
In this work, we formulate the image in-painting as a matrix completion problem. Traditional matrix completion methods are generally based on linear models, assuming that the matrix is low rank. When the original matrix is large scale and the observe...
We present a comparative study of three matrix completion and recovery techniques based on matrix inversion, gradient descent, and Lagrange multipliers, applied to the problem of human pose estimation. 3D human pose estimation algorithms may exhibit...
Compressed sensing is an alternative to Shannon/Nyquist sampling for acquiring sparse or compressible signals. Sparse coding represents a signal as a sparse linear combination of atoms, which are elementary signals derived from a predefined dictionar...
In our paper, we introduce a sparse and symmetric matrix completion quasi-Newton model using automatic differentiation, for solving unconstrained optimization problems where the sparse structure of the Hessian is available. The proposed method is a k...
More recently, the ability of the coprime array to yield large array apertures and high degrees of freedom in comparison with the uniform linear array (ULA) has drawn an enormous amount of attention. In light of this, we propose a low-rank matrix com...
In this work, we investigate the gridless parameter estimation of pulse–Doppler radar targets using a reduced number of samples under a limited bit budget. We propose a hybrid analog and digital (HAD) acquisition system integrating a tunable an...
We propose a method for estimating the channel matrix in MIMO communication systems from intermittent measurements based on the matrix completion technique. The method requires the minimization of the trace norm of the partially known channel matrix....
The quality of online services highly depends on the accuracy of the recommendations they can provide to users. Researchers have proposed various similarity measures based on the assumption that similar people like or dislike similar items or people,...
We consider a variant of the online semi-definite programming problem (OSDP). Specifically, in our problem, the setting of the decision space is a set of positive semi-definite matrices constrained by two norms in parallel: the
Lately, there has been a significant increase in interest in coprime array configurations, as they offer the advantage of generating more extensive array apertures and enhanced degrees of freedom when contrasted with standard linear arrays. This docu...
This study investigated the compressive behavior of 30 vol.% boron carbide (B4C)/2024 aluminum (Al) composites under quasi-static and dynamic loading at different temperatures. Building on the experimental findings, the Johnson–Cook (JC) model was mo...
In this paper, we consider complete homogeneous symmetric polynomials evaluated for variables repeated with given multiplicities; in other words, we consider polynomials obtained from complete homogeneous polynomials by identifying some subsets of th...
Insertion-deletion systems have been introduced as a formalism to model operations that find their counterparts in ideas of bio-computing, more specifically, when using DNA or RNA strings and biological mechanisms that work on these strings. So-calle...
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