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

Volume

4

fYear

2000

fDate

2000

Firstpage

373

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on

Conference_Location

Como

ISSN

1098-7576

Print_ISBN

0-7695-0619-4

Type

conf

DOI

10.1109/IJCNN.2000.860800

Filename

860800