Title :
NEURO-BRA: a bird removal approach for wind profiler data based on quantum neural networks
Author :
Kretzschmar, Ralf ; Karayiannis, Nicolaos B. ; Richner, Hans
Author_Institution :
Inst. for Signal & Inf. Process., Swiss Federal Inst. of Technol., Zurich, Switzerland
Abstract :
This paper presents the NEURO-BRA, a neural-network-based bird removal approach for wind profiler data. The NEURO-BRA was developed by training quantum neural networks to identify and remove bird-contaminated data recorded by a 1290-MHz wind profiler using a set of input features computed from the wind profiler measurements. This experimental investigation indicated that the NEURO-BRA was capable of removing over 90% of the bird-contaminated data recorded by the 1290-MHz wind profiler
Keywords :
Doppler radar; feature extraction; image recognition; learning (artificial intelligence); neural nets; radar imaging; wind; 1290 MHz; 3D wind field measurement; NEURO-BRA; bird removal; bird-contaminated data; feature selection; learning; quantum neural networks; vertical pulsed Doppler radar; wind profiler data; Birds; Clutter; Infrared detectors; Neural networks; Pollution measurement; Pulse measurements; Quantum computing; Rain; Signal to noise ratio; Time domain analysis;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.860800
