Výsledky vyhledávání

Reconstructing nonlinear networks subject to fast-varying noises by using linearization with expanded variables

Autor: Rundong Shi, Gang Hu, Shihong Wang

Publikováno v: Communications in Nonlinear Science and Numerical Simulation. 72:407-416

Reconstructing noise-driven nonlinear networks from time series of output variables is a challenging problem, which turns to be very difficult when nonlinearity of dynamics, strong noise impacts and low measurement frequencies jointly affect. In this

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d4a48cc28969006e321eb3b7d625759
https://doi.org/10.1016/j.cnsns.2019.01.010

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Analysis of the horizontal vibration response under gas–solid coupling throughout the entire high-speed elevator operating process

Autor: Rundong Shi, Qing Zhang, Ruijun Zhang, Qin He, Lixin Liu

Publikováno v: Journal of Vibration and Control. :107754632211184

High-speed elevator cars affected by external excitations exhibit complex horizontal vibration responses during their entire operating processes. To accurately explore the horizontal vibration response of a car and the response differences between th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ef77f553dac8134217959f9f3b293bc9
https://doi.org/10.1177/10775463221118410

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Boosting and Residual Learning Scheme with Pseudoinverse Learners

Autor: Xiaoxuan Sun, Rundong Shi, Ping Guo, Bo Zhao

Publikováno v: SMC

The traditional gradient descent based optimization algorithms for neural network are subjected too many vulnerabilities, such as slow convergent rate, gradient vanishing and falling into local minima. Therefore, the alternative non-gradient descent

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3a4680726e0da6d612b2705c99e2191b
https://doi.org/10.1109/smc42975.2020.9283232

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Detecting network structures from measurable data produced by dynamics with hidden variables

Autor: Rundong Shi, Shihong Wang, Weinuo Jiang

Publikováno v: Chaos (Woodbury, N.Y.). 30(1)

Depicting network structures from measurable data is of significance. In real-world situations, it is common that some variables of networks are unavailable or even unknown. These unavailable and unknown variables, i.e., hidden variables, will lead t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4173681b99a0be3cd89ef7f46032e093
https://pubmed.ncbi.nlm.nih.gov/32013512

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Detecting directed interactions of networks by random variable resetting

Autor: Shihong Wang, Changbao Deng, Rundong Shi

Publikováno v: EPL (Europhysics Letters). 124:18002

We propose a novel method of detecting directed interactions of a general dynamic network from measured data. By repeating random state variable resetting of a target node and appropriately averaging over the measurable data, the pairwise coupling fu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03f56fd2dee806e79ecb5f937aa59eae
https://doi.org/10.1209/0295-5075/124/18002

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