Neural networks are applied to the identi"cation of non-linear structural dynamic systems. Two complementary problems inspired from customer surveys are successively considered. Each of them calls for a di!erent neural approach. First, the mass of the system is identi"ed based on acceleration record
โฆ LIBER โฆ
Non-linear dynamics method for target identification
โ Scribed by Carroll, T.L.; Rachford, F.J.
- Book ID
- 117812788
- Publisher
- The Institution of Engineering and Technology
- Year
- 2011
- Tongue
- English
- Weight
- 258 KB
- Volume
- 5
- Category
- Article
- ISSN
- 1751-8784
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
NEURAL IDENTIFICATION OF NON-LINEAR DYNA
โ
R. LE RICHE; D. GUALANDRIS; J.J. THOMAS; F. HEMEZ
๐
Article
๐
2001
๐
Elsevier Science
๐
English
โ 401 KB
A METHOD FOR PARAMETER IDENTIFICATION OF
โ
J.S. TANG
๐
Article
๐
2000
๐
Elsevier Science
๐
English
โ 79 KB
A non-linear dynamic model identificatio
โ
Barry M. Wise; Dan Haesloop
๐
Article
๐
1995
๐
Elsevier Science
๐
English
โ 427 KB
A nonparametric method of identification
โ
Maciej Kulsiewicz
๐
Article
๐
1983
๐
Elsevier Science
๐
English
โ 544 KB
AN IDENTIFICATION TECHNIQUE FOR NON-LINE
โ
M. Kulisiewicz; R. Iwankiewicz; S. Piesiak
๐
Article
๐
1997
๐
Elsevier Science
๐
English
โ 310 KB
An identification technique is devised for SDOF dynamical mechanical systems under random excitations. The system is assumed to be governed by a non-linear equation of motion in general form, in which the restoring force and the dissipative terms are given by arbitrary power functions. Algebraic equ
A semi-analytical locally transversal li
โ
D. Roy; L. S. Ramachandra
๐
Article
๐
2001
๐
John Wiley and Sons
๐
English
โ 396 KB