Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Approach to the analysis of nonlinear dynamic systems structural identifiability (SI) under uncertainty is proposed. This approach has a difference from methods applied to SI estimation of dynamic systems in the parametrical space. Structural identifiability is interpreted as of the structural identification possibility a system nonlinear part. We show that the input should synchronize the system for the SI problem solution. The structural identifiability estimation method is based on the analysis of the framework special class. The input parameter effect on the possibility of the SI estimation of the system is studied.
Nikolay Karabutov. 2018. \u201cAbout Structural Identifiability of Nonlinear Dynamic Systems under Uncertainty\u201d. Global Journal of Science Frontier Research - A: Physics & Space Science GJSFR-A Volume 18 (GJSFR Volume 18 Issue A11): .
Crossref Journal DOI 10.17406/GJSFR
Print ISSN 0975-5896
e-ISSN 2249-4626
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Total Score: 101
Country: Unknown
Subject: Global Journal of Science Frontier Research - A: Physics & Space Science
Authors: Nikolay Karabutov (PhD/Dr. count: 0)
View Count (all-time): 146
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Publish Date: 2018 11, Thu
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Approach to the analysis of nonlinear dynamic systems structural identifiability (SI) under uncertainty is proposed. This approach has a difference from methods applied to SI estimation of dynamic systems in the parametrical space. Structural identifiability is interpreted as of the structural identification possibility a system nonlinear part. We show that the input should synchronize the system for the SI problem solution. The structural identifiability estimation method is based on the analysis of the framework special class. The input parameter effect on the possibility of the SI estimation of the system is studied.
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