A neural clustering approach for high resolution radar target classification

Pattern Recognition

Volumn 27, Issue 4, 1994, Pages 503-513

  Stewart, Clayton ^a   Lu, Yi Chuan ^a   Larson, Victor ^a  

^a GEORGE MASON UNIVERSITY   (United States)

Author keywords

Artificial neural networks; Automatic target recognition; Learning vector quantization; Self organizing maps

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS; RADAR IMAGING; VECTORS;

AUTOMATIC TARGET RECOGNITION; CLUSTERING; LEARNING VECTOR QUANTIZATION; SELF ORGANIZING FEATURE MAPS;

PATTERN RECOGNITION;

EID: 0028416679     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/0031-3203(94)90032-9     Document Type: Article

References (6)

1. A comparison of 1-D and 2-D algorithms for radar target classification
2. The Self-Organizing Map
3. Learning vector quantization
4. Automatic formation of topological maps of patterns in a self-organizing system
5. A Nonlinear Mapping for Data Structure Analysis
6. Vector quantization and learning vector quantization for radar target classification