A feedforward backpropagation neural network is formed to identify the stability characteristic of a high speed rotordynamic system. The principal focus resides in accounting for the instability due to the bearing clearance effects. The abnormal operating condition of 'normal-loose' Coulomb rub, tha
β¦ LIBER β¦
Neural classifiers for dynamic system modes
β Scribed by W.A. Porter
- Publisher
- Elsevier Science
- Year
- 1995
- Tongue
- English
- Weight
- 875 KB
- Volume
- 82
- Category
- Article
- ISSN
- 0020-0255
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
A classifier neural network for rotordyn
β
R. Ganesan; Jin Jionghua; T.S. Sankar
π
Article
π
1995
π
Elsevier Science
π
English
β 633 KB
Distributed and local neural classifiers
β
F. GΓΌrgen; R. Alpaydin; U. ΓnlΓΌakin; E. Alpaydin
π
Article
π
1994
π
Elsevier Science
π
English
β 613 KB
A probabilistic model for evaluation of
β
M.T. Musavi; K.H. Chan; D.M. Hummels; K. Kalantri; W. Ahmed
π
Article
π
1992
π
Elsevier Science
π
English
β 842 KB
A new fast algorithm for effective train
β
Wen-Shou Chou; Yung-Chang Chen
π
Article
π
1992
π
Elsevier Science
π
English
β 503 KB
Comparing BP and ARt II neural network c
β
Colin O. Benjamin; Sheng-Chai Chi; Tarek Gaber; Catherine A. Riordan
π
Article
π
1995
π
Elsevier Science
π
English
β 565 KB
Counting and Classifying Attractors in H
β
R.J. Bagley; Leon Glass
π
Article
π
1996
π
Elsevier Science
π
English
β 381 KB
Randomly connected Boolean networks have been used as mathematical models of neural, genetic, and immune systems. A key quantity of such networks is the number of basins of attraction in the state space. The number of basins of attraction changes as a function of the size of the network, its connect