DocumentCode
3005933
Title
Bearing estimation using neural networks
Author
Jha, S. ; Chapman, R. ; Durrani, T.S.
Author_Institution
Dept. of Electron. & Electr. Eng., Strathclyde Univ., Glasgow, UK
fYear
1988
fDate
11-14 Apr 1988
Firstpage
2156
Abstract
Two modifications to the neural-network algorithm originally proposed by J.J. Hopfield (1982), gain annealing and iterated descent, are proposed that yield better convergence to the global minimum. Simulation results are presented to illustrate the performance of the proposed algorithm for bearing estimation
Keywords
convergence; estimation theory; iterative methods; minimisation; neural nets; bearing estimation; convergence; gain annealing; global minimum; iterated descent; neural networks; simulation results; Convergence; Covariance matrix; Direction of arrival estimation; Image converters; Matrix decomposition; Neural networks; Neurons; Sensor arrays; Signal processing algorithms; Simulated annealing;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on
Conference_Location
New York, NY
ISSN
1520-6149
Type
conf
DOI
10.1109/ICASSP.1988.197059
Filename
197059
Link To Document