Collaborative filtering (CF) is a widely used method in recommendation systems. Linear models are still the mainstream of collaborative filtering research methods, but non-linear probabilistic models are beyond the limit of linear model capacity. For...
Polymer processes often contain state variables whose distributions are multimodal; in addition, the models for these processes are often complex and nonlinear with uncertain parameters. This presents a challenge for Kalman-based state estimators suc...
To address the problem of unclear images affected by occlusion from fog, we propose an improved Retinex image enhancement algorithm based on the Gaussian pyramid transformation. Our algorithm features bilateral filtering as a replacement for the Gaus...
The spatially modulated full-polarization imaging system encodes complete polarization information into a single interferogram, enabling rapid demodulation. However, traditional single Gaussian low-pass filtering cannot adequately suppress crosstalk...
In hidden Markov chain (HMC) models, widely used for target tracking, the process noise and measurement noise are in general assumed to be independent and Gaussian for mathematical simplicity. However, the independence and Gaussian assumptions do not...
Nowadays, the increasing demands of location-based services (LBS) have spurred the rapid development of indoor positioning systems (IPS). However, the performance of IPSs is affected by the fluctuation of the measured signal. In this study, a Gaussia...
This paper investigates the filtering problem for multivariate continuous nonlinear non-Gaussian systems based on an improved minimum error entropy (MEE) criterion. The system is described by a set of nonlinear continuous equations with non-Gaussian...
Although compressed sensing theory has many advantages in image reconstruction, its reconstruction and sampling time is very long. Fast reconstruction of high-quality images at low measurement rates is the direction of the effort. Compressed sensing...
This study aims to quantify the shear surface morphology of jointed rock and its evolution under shearing, cyclic freezing, and thawing using the Gaussian filtering method. Gaussian filtering method enables the construction of the (large-scale) wavin...
Falls are a significant health concern leading to increased morbidity and healthcare costs, especially for the elderly. Early and accurate detection of fall events is critical for timely intervention and preventing severe complications. This study pr...
Frequency estimation plays a critical role in vital sign monitoring. Methods based on Fourier transform and eigen-analysis are commonly adopted techniques for frequency estimation. Because of the nonstationary and time-varying characteristics of phys...
The inner surface of engine cylinder liners has a plateau structure because of being required to have excellent sliding properties. To improve the tribological properties, the plateau surface consists of a smooth plateau region and a valley region wh...
This paper addresses the problem of tracking multiple extended targets in three-dimensional space. We propose the Gaussian process Gaussian mixture probability hypothesis density (GP-PHD) filter, which is capable of tracking multiple extended targets...
In a non-Gaussian environment, the accuracy of a Kalman filter might be reduced. In this paper, a two- dimensional Monte Carlo Filter is proposed to overcome the challenge of the non-Gaussian environment for filtering. The two-dimensional Monte Carlo...
Color noise is a special kind of noise often occurring in localization systems, and it is more suitable than the general Gaussian white noise to model time dependence due to time delay or high-frequency sampling. This paper derives a nonlinear Gaussi...
This paper presents a fully non-Gaussian filter for sequential data assimilation. The filter is named the “cluster sampling filter”, and works by directly sampling the posterior distribution following a Markov Chain Monte-Carlo (MCMC) app...
The evaluation of baroreflex sensitivity (BRS) has proven to be critical for medical applications. The use of α indices by spectral methods has been the most popular approach to BRS estimation. Recently, an algorithm termed Gaussian average fil...
In this paper, we investigate the state estimation of systems with unknown covariance non-Gaussian measurement noise. A novel improved Gaussian filter (GF) is proposed, where the maximum correntropy criterion (MCC) is used to suppress the pollution o...
In this paper, the resilient minimum entropy filter problem is investigated for the stochastic systems with non-Gaussian disturbances. The goal of designing the filter is to guarantee that the entropy of the estimation error is monotonically decreasi...
When analyzing vibration or acoustic signals in machinery, noise interference within the characteristic signals can significantly distort the results. This issue is particularly pronounced in complex environments, where mechanical signals are often o...
Gaussian filtering, being a convolution with a Gaussian kernel, is a widespread technique in image analysis and computer vision applications. It is the traditional approach for noise reduction. In some cases, performing the exact convolution can be c...
As one of the most critical issues for target track,
The underwater motion of the ROV is affected by various environmental factors, such as wind, waves, and currents. The complex relationship between these disturbance variables results in non-Gaussian noise distribution, which cannot be handled by the...
Kalman filtering is a linear quadratic estimation (LQE) algorithm that uses a time series of observed data to produce estimations of unknown variables. The Kalman filter (KF) concept is widely used in applied mathematics and signal processing. In thi...
In-cell touch and display integrated panels, along with their integrated readout systems, are widely adopted in mobile devices for their cost-effectiveness and compact design. This paper proposes an analog Gaussian-shaped filter and a current mode co...
In this paper, we propose a new technique—called Ellipsoidal and Gaussian Kalman filter—for state estimation of discrete-time nonlinear systems in situations when for some parts of uncertainty, we know the probability distributions, while...
Magnetic resonance sounding is a geophysical method for quantitatively determining the state for groundwater storage that has gained international attention in recent years. However, the practical acquisition of magnetic resonance sounding signals, w...
This paper proposes a deep learning model that integrates a convolutional neural network with a gate circulation unit that captures patterns of high-peak PM2.5 concentrations. The purpose is to accurately predict high-peak PM2.5 concentration data th...
With the continuous advancement of target detection technology in remote sensing, target detection technology in images captured by drones has performed well. However, object detection in drone imagery is still a challenge under rainy conditions. Rai...
Detecting the defects of a battery on the surface and edge has always been difficult, especially for concave and convex ones, thereby seriously affecting its quality. Thus, sub-regional Gaussian and moving average filtering are innovatively proposed...
Multi-source heterogeneous information fusion based on the Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS)/odometer is an important technical means to solve the problem of navigation and positioning in complex environments....
The presence of strong noise and vibration interference in fault vibration signals poses challenges for extracting fault features from motor bearings. Therefore, appropriate pre-filtering procedures can effectively suppress the impact of the noise in...
Some advantages of using cameras as sensor devices on feedback systems are the flexibility of the data it represents, the possibility to extract real-time information, and the fact that it does not require contact to operate. However, in unstructured...
Denoising computed tomography (CT) medical images is crucial in preserving information and restoring images contaminated with noise. Standard filters have extensively been used for noise removal and fine details’ preservation. During the transm...
Kalman filter is a well-established accuracy correction method in control, guidance, and navigation. With the popularity of mobile communication and ICT, Kalman Filter has been used in many new applications related to positioning based on spatiotempo...
Convolutional neural networks leverage their efficient ability to extract common features of images, playing a crucial role in numerous computer vision tasks. Key details such as edges and textures in images often present themselves in the form of hi...
With the growing deployment of autonomous driving and unmanned systems in road environments, efficiently and accurately performing environmental perception and map construction has become a significant challenge for SLAM systems. In this paper, we pr...
Multimodal images refer to images obtained by different sensors, and there are serious nonlinear radiation differences (NRDs) between multimodal images for photos of the same object. Traditional multimodal image matching methods cannot achieve satisf...
Global Navigation Satellite Systems (GNSSs) observables, such as those of the Global Positioning System (GPS), are frequently affected by multipath effects that cause unpredictable signal interference at the receiver, posing significant challenges fo...
This work proposes an analytical design procedure for a particular class of 2D filters, namely anisotropic Gaussian FIR filters. The design is achieved in the frequency domain and starts from a low-pass Gaussian 1D prototype with imposed specificatio...
In this paper, the application of the Gaussian Kernel Smoothing Filter (GKSF) in the field of structural health monitoring (SHM) for bridges is explored. A baseline-free, GKSF-based method is developed to detect and localize structural damage in brid...
All around the world, partial or total blindness has become a direct consequence of diabetes and hypertension. Visual disorders related to these diseases require automatic and specialized methods to detect early malformations, artifacts, or irregular...
A cooperative dynamic range-only simultaneous localization and mapping (CDRO-SLAM) algorithm based on the sum of Gaussian (SoG) filter was recently introduced. The main characteristics of the CDRO-SLAM are (i) the integration of inter-node ranges as...
For the bearing-only target motion analysis (TMA), the pseudolinear Kalman filter (PLKF) solves the complex nonlinear estimation of the motion model parameters but suffers serious bias problems. The pseudolinear Kalman filter under the minimum mean s...
Real-time imitation enables a humanoid robot to mirror the behavior of humans, being important for applications of human–robot interaction. For imitation, the corresponding joint angles of the humanoid robot should be estimated. Generally, a humanoid...
Capacitive touch panels (CTPs) have the merits of being waterproof, antifouling, scratch resistant, and capable of rapid response, making them more popular in various touch electronic products. However, the CTP has a multilayer structure, and the bac...
In this paper, we propose a robotic arm grasping system suitable for complex environments. For a robotic arm, in order to achieve its accurate grasp of the target object, not only the vision but also a certain tracking ability should be provided. To...
This paper introduces a Linear Quadratic Gaussian (LQG) controller for a Single-Ended Primary Inductor Converter (SEPIC). The LQG design is based on merging an integral Linear Quadratic Regulator (LQR) with an offline Kalman Filter (commonly referred...
Accurate prediction of the remaining useful life (RUL) of lithium–ion batteries is the focus of lithium–ion battery health management. To achieve high–precision RUL estimation of lithium–ion batteries, a novel RUL prediction model is proposed by comb...
Flying bird detection has recently attracted increasing attention in computer vision. However, compared to conventional object detection tasks, it is much more challenging to trap flying birds in infrared videos due to small target size, complex back...
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