Feature Extraction Based on Manifold Learning for Radio Fingerprint

Keyphrases

• Computational Complexity 50%
• Dimensionality Reduction 50%
• Estimation Method 50%
• Feature Extraction 100%
• Feature Extraction Methods 50%
• Fingerprint Database 50%
• Fingerprint Feature 50%
• High Dimension 50%
• Indoor Localization 50%
• Intrinsic Dimension Estimation 50%
• Large-scale Environment 100%
• Manifold Learning 100%
• Network Fingerprinting 50%
• Offline Database 50%
• Out-of-sample Extension 50%
• Position Accuracy 50%
• Positioning Accuracy 50%
• Problem Complexity 50%
• Radio Frequency Fingerprint 100%
• Received Signal Strength 50%
• Reduction Technologies 50%
• Storage Problem 50%
• T-distributed Stochastic Neighbor Embedding (t-SNE) 50%
• Wireless Local Area Network 50%

Computer Science

• Computational Complexity 50%
• Dimensionality Reduction 50%
• Estimation Method 50%
• Extension Method 50%
• Feature Extraction 100%
• Fingerprint Database 50%
• High Dimensionality 50%
• Intrinsic Dimensionality 50%
• Manifold Learning 100%
• Problem Complexity 50%
• Received Signal Strength 50%
• T-Distributed Stochastic Neighbor Embedding 50%
• wireless local area network 50%

Engineering

• Based Feature Extraction 100%
• Computational Complexity 14%
• Dimensionality 100%
• Feature Extraction 14%
• Intrinsic Dimensionality 14%
• Local Area Network 14%
• Received Signal Strength 14%