LPV system identification using the matchable observable linear identification approach

Mathematics

• System Identification 87%
• Predictors 65%
• Optimal Prediction 41%
• Prediction Error 33%
• Least Squares Support Vector Machine 23%
• Unknown Parameters 20%
• Error Estimator 16%
• Output 15%
• Linear regression 13%
• Estimator 12%
• 2-D Systems 9%
• Linear Least Squares 8%
• Form 8%
• State-space Model 8%
• Kernel Function 7%
• Discrete-time Systems 7%
• Least Square Method 7%
• Scheduling 7%
• Parameterization 7%
• White noise 7%
• Basis Functions 6%
• Disturbance 6%
• Linear Function 6%
• Linear Combination 6%
• Prediction 5%
• Regression 5%
• Formulation 4%
• Model 2%
• Class 2%

Business & Economics

• System Identification 100%
• Predictors 76%
• Prediction Error 35%
• Estimator 28%
• Least Squares Support Vector Machine 22%
• Linear Regression 14%
• State-space Model 12%
• Kernel 8%
• Least Square Method 8%
• Discrete-time 7%
• Matrix 6%
• Prediction 5%

Engineering & Materials Science

• Identification (control systems) 62%
• Linear regression 28%
• Support vector machines 22%
• White noise 15%
• Parameterization 15%
• Scheduling 9%