A Novel Fractional Tikhonov Regularization Coupled with an Improved Super-Memory Gradient Method and Application to Dynamic Force Identification Problems
This paper presents a novel inverse technique to provide a stable optimal solution for the ill-posed dynamic force identification problems. Due to ill-posedness of the inverse problems, conventional numerical approach for solutions results in arbitrarily large errors in solution. However, in the fie...
Main Authors: | Nengjian Wang, Chunping Ren, Chunsheng Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2018-01-01
|
Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2018/4790950 |
Similar Items
-
Dynamic Force Identification Problem Based on a Novel Improved Tikhonov Regularization Method
by: Chunping Ren, et al.
Published: (2019-01-01) -
Load Identification Method Based on Interval Analysis and Tikhonov Regularization and Its Application
by: Chunsheng Liu, et al.
Published: (2019-01-01) -
Identification of Random Dynamic Force Using an Improved Maximum Entropy Regularization Combined with a Novel Conjugate Gradient
by: ChunPing Ren, et al.
Published: (2017-01-01) -
Research on Coal-Rock Fracture Image Edge Detection Based on Tikhonov Regularization and Fractional Order Differential Operator
by: Chunsheng Liu, et al.
Published: (2019-01-01) -
A Novel Method of Dynamic Force Identification and Its Application
by: Nengjian Wang, et al.
Published: (2019-01-01)