Zobrazeno 1 - 8
of 8
pro vyhledávání: '"RunDong Shi"'
Publikováno v:
Multimedia Tools and Applications.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf81563a2e3817db053a9bb408de1535
https://doi.org/10.1007/s11042-022-14087-1
https://doi.org/10.1007/s11042-022-14087-1
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8b9555f9a4e631387d083a469f2ae0d
https://doi.org/10.1145/3534678.3539295
https://doi.org/10.1145/3534678.3539295
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
https://doi.org/10.1016/j.cnsns.2019.01.010
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
https://doi.org/10.1177/10775463221118410
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
https://doi.org/10.1109/smc42975.2020.9283232
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
https://pubmed.ncbi.nlm.nih.gov/32013512
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
https://doi.org/10.1209/0295-5075/124/18002
Publikováno v:
Europhysics Letters; Oct2018, Vol. 124 Issue 1, p1-1, 1p