Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Chunbo Xiu"'
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7843 (2024)
In the complex clutter background, the clutter center frequency is not fixed, and the spectral width is wide, which leads to the performance degradation of the traditional adaptive clutter suppression method. Therefore, an adaptive clutter intelligen
Externí odkaz:
https://doaj.org/article/6bb87068323d4b489749c09270aa28ff
Publikováno v:
Sensors, Vol 24, Iss 14, p 4708 (2024)
In modern radar detection systems, the particle filter technique has become one of the core algorithms for real-time target detection and tracking due to its good nonlinear and non-Gaussian system state estimation capability. However, when dealing wi
Externí odkaz:
https://doaj.org/article/51dba3a9322647e1b95ef6cdda5c8605
Autor:
Chunbo Xiu, Yunfei Ma
Publikováno v:
IET Image Processing, Vol 16, Iss 4, Pp 937-947 (2022)
Abstract Aiming at the problem that the tracking performance of the traditional kernel correlation filter tracking algorithm is easy to be affected by illumination variation, occlusion and motion blur during tracking, an improved tracking strategy is
Externí odkaz:
https://doaj.org/article/791e966335c84a238337dc44fc351de8
Publikováno v:
IEEE Access, Vol 8, Pp 29501-29507 (2020)
Weibull clutter is used as an example in this paper. Based on the serial parallel analysis of Zero-memory non-linear transformation's Weibull distributed clutter algorithm, fine-grained optimization is performed. The fine-grained part uses the cuBLAS
Externí odkaz:
https://doaj.org/article/efb3c6fe085943a3b244ce96fdf1b04f
Publikováno v:
IEEE Access, Vol 7, Pp 25972-25979 (2019)
The border regression is a key technique of the regional convolution neural network (CNN) to locate the target. However, it relies on the border label information of a large number of sample data. Therefore, it is inefficient to generate the training
Externí odkaz:
https://doaj.org/article/85cf10cd63c24b389443569dcd5e362e
Autor:
Chunbo Xiu, Xuemiao Su
Publikováno v:
IEEE Access, Vol 7, Pp 117814-117828 (2019)
In order to improve the noise reduction performance and the clarity of denoising images, a composite convolutional neural network composed of the convolutional autoencoder network and the feature reconstruction network is proposed. Multiple convoluti
Externí odkaz:
https://doaj.org/article/f81d1d8a7f80408bb05e66b7bb1c0a7a
Autor:
Chunbo Xiu, Xin Li
Publikováno v:
IEEE Access, Vol 7, Pp 90750-90759 (2019)
In order to extract more texture and detail information from a given image, a memristor cell neural network is proposed by replacing the state resistances of the neurons as the memristors. The characteristic of memristor could be maintained in the wh
Externí odkaz:
https://doaj.org/article/4f53f879d89a49169e1c5a0a6d5a8a1a
Autor:
Chunbo Xiu, Ruosi Wang
Publikováno v:
IEEE Access, Vol 6, Pp 33819-33825 (2018)
In order to improve the control performance of the transport vehicle, the dynamic model, instead of the kinematic model, is established. The equation of state can be divided into two independent subsystems: the speed sub system and the attitude angle
Externí odkaz:
https://doaj.org/article/ed73863df3a642ea80f8838f43ef5239
Autor:
Chunbo Xiu, Penghui Guo
Publikováno v:
IEEE Access, Vol 6, Pp 49793-49800 (2018)
In order to overcome the disadvantages of the conventional sliding mode reaching law, such as the large chattering and the slow convergence rate, an improved quick reaching law is proposed. The reaching law is composed of two terms which can, respect
Externí odkaz:
https://doaj.org/article/bbb8aec36233478e9cfefb2911771247
Publikováno v:
IEEE Access, Vol 4, Pp 8617-8624 (2016)
A chaotic neuron with hysteretic and creep characteristics is proposed based on the conventional chaotic neuron model, with which a neural network is constructed, and the synchronous control between the hysteretic creep chaotic neuron or neural netwo
Externí odkaz:
https://doaj.org/article/2d10503b9ae34b51a387d63eb95d5a15