Results 41 to 50 of about 134,664 (159)
A GEDMM is proposed to represent the MIWPS as multiple VSISs and model each of them as the VTDS2M whose unknown parameters are identified with the proposed hybrid optimized square root cubature Kalman filter (HOSRCKF). To solve the issues that the physical meanings of existing short circuit ratios (SCRs) are unclear and the critical values of existing ...
Mengxian Sun +3 more
wiley +1 more source
Discrete transforms and orthogonal polynomials of (anti)symmetric multivariate cosine functions
The discrete cosine transforms of types V--VIII are generalized to the antisymmetric and symmetric multivariate discrete cosine transforms. Four families of discretely and continuously orthogonal Chebyshev-like polynomials corresponding to the ...
Hrivnák, Jiří, Motlochová, Lenka
core +1 more source
Adaptive High Manoeuvring Target Tracking Algorithm Based on CNN‐LSTM Fusion Architecture
To solve the problems of model switching lag and tracking accuracy decline in interacting multiple model (IMM) algorithm in complex manoeuvring target tracking, an adaptive interacting multiple model unscented Kalman filter (IMM‐UKF) algorithm based on convolutional neural network and long short‐term memory network (CNN‐LSTM) fusion architecture is ...
Yuhan Cui +3 more
wiley +1 more source
Approximate Approximations from scattered data
The aim of this paper is to extend the approximate quasi-interpolation on a uniform grid by dilated shifts of a smooth and rapidly decaying function on a uniform grid to scattered data quasi-interpolation.
Lanzara, F., Maz'ya, V., Schmidt, G.
core +1 more source
To address the limitations of existing wireless and inertial navigation systems, this paper proposes a high‐precision integrated positioning scheme based on particle filtering. The method introduces a high‐weight particle neighbourhood attraction mechanism to solve the common issue of particle degeneracy.
Yanbiao Gao, Zhongliang Deng
wiley +1 more source
BP Neural Network–Based Kalman Filtering Method Under Multiple Cyberattacks
This paper proposes a Kalman‐gain‐driven neural Kalman filtering (KF) defense framework, termed KFDBP, for secure state estimation in cyber–physical systems (CPSs) under denial‐of‐service (DoS), spoofing, and replay attacks. Unlike end‐to‐end neural filtering approaches such as KalmanNet that directly learn state estimators or implicitly approximate ...
Zijing Li +7 more
wiley +1 more source
Moments from their very truncations
It is known that positive definiteness is not enough for the multidimensional moment problem to be solved. We would like throw in to the garden of existing in this matter so far results one more, a result which takes into considerations the utmost ...
Szafraniec, F. H.
core +1 more source
The implementation of Kalman filter (KF) in tracking high‐dimensional, strongly correlated graph structured data is often complex and unstable. Meanwhile, in practical applications, the system may be subject to interference from non‐Gaussian noise and various cyberattacks.
Bingyu Yin, Xinmin Song, Wenling Li
wiley +1 more source
Markov cubature rules for polynomial processes
We study discretizations of polynomial processes using finite state Markov processes satisfying suitable moment matching conditions. The states of these Markov processes together with their transition probabilities can be interpreted as Markov cubature ...
Filipović, Damir +2 more
core +2 more sources
Vehicle sideslip angle is one of the irreplaceable variable indicators for evaluating vehicle stability. However, it is difficult to directly measure vehicle sideslip angle with onboard sensors. In order to obtain precise vehicle sideslip angle using onboard sensors, a novel observation strategy based on fusion of steady‐state model method and square ...
Zhendong Zhu +3 more
wiley +1 more source

