Zobrazeno 1 - 10
of 325
pro vyhledávání: '"Chenglin Wen"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-16 (2023)
Abstract Existing low-light image enhancement techniques face challenges in achieving high visual quality and computational efficiency, as well as in effectively removing noise and adjusting illumination in extremely dark scenes. To address these pro
Externí odkaz:
https://doaj.org/article/9795d90e5e694fd0ad0bcfe29833de8f
Publikováno v:
ACS Omega, Vol 8, Iss 41, Pp 38013-38024 (2023)
Externí odkaz:
https://doaj.org/article/b6d8b5a36a82455d89a8a4a4dd6dbafc
Autor:
Linwang Ding, Chenglin Wen
Publikováno v:
Symmetry, Vol 16, Iss 5, p 617 (2024)
In general, the extended Kalman filter (EKF) has a wide range of applications, aiming to minimize symmetric loss function (mean square error) and improve the accuracy and efficiency of state estimation. As the nonlinear model complexity increases, ro
Externí odkaz:
https://doaj.org/article/2e37aaed842541bb9f891ee08cdf59cb
Autor:
Chengyi Li, Chenglin Wen
Publikováno v:
Actuators, Vol 13, Iss 5, p 169 (2024)
In the actual working environment, most equipment models present nonlinear characteristics. For nonlinear system filtering, filtering methods such as the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Cubature Kalman Filter (CKF) ha
Externí odkaz:
https://doaj.org/article/09b1b70a02cc49c79a1c8c1a7c6f3bd3
Autor:
Haiyang Zhang, Chenglin Wen
Publikováno v:
Mathematics, Vol 12, Iss 8, p 1168 (2024)
The cubature Kalman filter (CKF) cannot accurately estimate the nonlinear model, and these errors will have an impact on the accuracy. In order to improve the filtering performance of the CKF, this paper proposes a new CKF method to improve the estim
Externí odkaz:
https://doaj.org/article/60087ad63aaa489c998b98a0b730cb6a
Publikováno v:
Mathematics, Vol 12, Iss 1, p 137 (2023)
This paper proposes a Kalman filter for linear rectangular singular discrete-time systems, where the singular matrix in the system is a rectangular matrix without full column rank. By using two different restricted equivalent transformation methods a
Externí odkaz:
https://doaj.org/article/d8748b9fb496404e94134933c05d9d58
Publikováno v:
ACS Omega, Vol 7, Iss 8, Pp 6978-6990 (2022)
Externí odkaz:
https://doaj.org/article/377b52e3b2be46debdce6c88aa845199
Publikováno v:
Entropy, Vol 25, Iss 8, p 1165 (2023)
Federated learning (FL) is an effective method when a single client cannot provide enough samples for multiple condition fault diagnosis of bearings since it can combine the information provided by multiple clients. However, some of the client’s wo
Externí odkaz:
https://doaj.org/article/e21272740cca4f25a12e2c8fc8cc5440
Publikováno v:
Sensors, Vol 23, Iss 6, p 2894 (2023)
A high-order Kalman filter for full-dimensional variables is proposed for a class of dynamic systems whose state model and measurement model are both nonlinear. The filter requires Taylor expansion of the system equations, and then performs Kronecker
Externí odkaz:
https://doaj.org/article/df42f6bab40846158e52caf3fc308473
Autor:
Li Yang, Chenglin Wen
Publikováno v:
IEEE Access, Vol 9, Pp 51679-51688 (2021)
Recently, public attention is thoroughly aroused as to the security threats of Wireless Network Control System (WNCS), which can seriously disrupt the system operation. In order to achieve the attack effect that each sensor is damaged and maximize th
Externí odkaz:
https://doaj.org/article/75d6a1f27cca41f1b08a949b883b0099