Zobrazeno 1 - 10
of 210
pro vyhledávání: '"Hua-Liang Wei"'
Publikováno v:
Meteorological Applications, Vol 31, Iss 1, Pp n/a-n/a (2024)
Abstract Dynamical seasonal forecast models are improving with time but tend to underestimate the amplitude of atmospheric circulation variability and to have lower skill in predicting summer variability than in winter. Here, we construct Nonlinear A
Externí odkaz:
https://doaj.org/article/dec23f2db9f54946bc11a9aeb87ce901
Publikováno v:
Frontiers in Neuroscience, Vol 17 (2023)
Externí odkaz:
https://doaj.org/article/2f135d2aef2a4096aed5ff2d8cbcf416
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 4, Pp 375-389 (2023)
The application of wind power is greatly restricted due to the volatility and intermittency of wind. It is a challenging task to quantify the uncertainty of wind speed prediction. To tackle such a challenge, an adaptive interval construction-based ga
Externí odkaz:
https://doaj.org/article/d06be3bfc49f4534b0f409343d644579
Publikováno v:
IEEE Open Journal of Power Electronics, Vol 3, Pp 368-381 (2022)
With the use of sensorless control strategy, mechanical position sensors can be removed from the gearbox, so as to decrease the maintenance costs and enhance the system robustness. In this paper, a switching PI control based model reference adaptive
Externí odkaz:
https://doaj.org/article/b7e77bd404884105a85e6b007c8deb8d
Publikováno v:
Sensors, Vol 22, Iss 15, p 5863 (2022)
Joint detection and embedding (JDE) methods usually fuse the target motion information and appearance information as the data association matrix, which could fail when the target is briefly lost or blocked in multi-object tracking (MOT). In this pape
Externí odkaz:
https://doaj.org/article/9023e1e1f73a42ef9496b972246f15f3
Publikováno v:
IEEE Access, Vol 6, Pp 17826-17840 (2018)
A new transient Granger causality detection method is proposed based on a time-varying parametric modeling framework, and is applied to the real EEG signals to reveal the causal information flow during motor imagery (MI) tasks. The time-varying param
Externí odkaz:
https://doaj.org/article/b05ad3914bb24814b626e81abe44d1d6
Publikováno v:
Systems Science & Control Engineering, Vol 6, Iss 1, Pp 319-328 (2018)
This paper is concerned with the model selection and model averaging problems in system identification and data-driven modelling for nonlinear systems. Given a set of data, the objective of model selection is to evaluate a series of candidate models
Externí odkaz:
https://doaj.org/article/5222c7f5d8944c9fa9eb9b40b2cfd456
Publikováno v:
Sensors, Vol 21, Iss 5, p 1839 (2021)
Fisheye images with a far larger Field of View (FOV) have severe radial distortion, with the result that the associated image feature matching process cannot achieve the best performance if the traditional feature descriptors are used. To address thi
Externí odkaz:
https://doaj.org/article/1fea1dc795e4474595dbc2fa76d93fdc
Publikováno v:
Sensors, Vol 20, Iss 15, p 4349 (2020)
Standard convolutional filters usually capture unnecessary overlap of features resulting in a waste of computational cost. In this paper, we aim to solve this problem by proposing a novel Learned Depthwise Separable Convolution (LdsConv) operation th
Externí odkaz:
https://doaj.org/article/a32126f6548349108ab928d2d247f50c
Publikováno v:
Sensors, Vol 19, Iss 2, p 387 (2019)
In recent years, regression trackers have drawn increasing attention in the visual-object tracking community due to their favorable performance and easy implementation. The tracker algorithms directly learn mapping from dense samples around the targe
Externí odkaz:
https://doaj.org/article/3d8d58cbb2fb4caba9a489f6cc2114d5