Abstract
A set of features are derived from scattered fields calculated by using the image technique formulation and method of moment (MoM) and a database is formed by using two cylindrical targets at certain angles. After the application of wavelet transform for feature extraction from this database, the coefficients of the signal are used as the inputs of the artificial neural networks. The real performances of the networks are investigated by ROC (receiver operating characteristic) analysis. This work aims to diminish the size of the database smaller by wavelet transform for finding the corresponding cylindrical target from the scattered field values.
Keywords
Wavelet transform
Wavelet
Feature extraction
Artificial intelligence
Pattern recognition (psychology)
Feature (linguistics)
Receiver operating characteristic
Moment (physics)
Computer science
Field (mathematics)
Set (abstract data type)
Wavelet packet decomposition
Image (mathematics)
Artificial neural network
Mathematics
Physics
Subject Areas
Optical measurement and interference techniques
·Computer Vision and Pattern Recognition ·Physical Sciences
Infrared Target Detection Methodologies
·Aerospace Engineering ·Physical Sciences
Optical Polarization and Ellipsometry
·Biomedical Engineering ·Physical Sciences
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