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
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;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on
Conference_Location :
New York, NY
DOI :
10.1109/ICASSP.1988.197059
