Online extreme learning on fixed-point sensor networks

Keyphrases

• Recursive Least Squares 100%
• Online Sequential Extreme Learning Machine (OSELM) 100%
• Sensor Networks 100%
• Point Sensor 100%
• Extreme Learning 100%
• Anomaly Detection 66%
• Prediction Accuracy 33%
• Limited Resources 33%
• Embedded Systems 33%
• Sensor Data 33%
• Rule-based Method 33%
• Linear Least Squares Estimation 33%
• Wireless Sensor Networks 33%
• Correction Mechanism 33%
• Communication Overhead 33%
• Stability Issues 33%
• Anomaly Detection System 33%
• Numerical Stability 33%
• Local Computation 33%
• Fixed Precision 33%
• Detection Accuracy 33%
• Online Learning Algorithm 33%
• Single Hidden Layer Neural Network 33%
• Generalization Properties 33%
• Hardware Resources 33%
• Embedded Implementation 33%

Engineering

• Point Sensor 100%
• Fixed Points 100%
• Sensor Network 100%
• Least Square 80%
• Recursive 60%
• Extreme Learning Machine 60%
• Anomaly Detection 40%
• Experimental Result 20%
• Limited Resource 20%
• Nodes 20%
• Sensor Data 20%
• Online Learning Algorithm 20%
• Feedforward 20%
• Numerical Stability 20%
• Wireless Sensor Network 20%
• Detection Algorithm 20%

Computer Science

• Sensor Networks 100%
• Fixed Points 100%
• Extreme Learning Machine 60%
• recursive least square 60%
• Anomaly Detection 40%
• Least Squares Methods 20%
• Wireless Sensor Network 20%
• Embedded Systems 20%
• Prediction Accuracy 20%
• Communication Overhead 20%
• Hardware Resource 20%
• Detection Accuracy 20%
• Learning Algorithm 20%
• Detection Algorithm 20%
• Feed Forward Neural Networks 20%
• Experimental Result 20%