Treść książki
Przejdź do opcji czytnikaPrzejdź do nawigacjiPrzejdź do informacjiPrzejdź do stopki
4
3.6.Modelorderestimation//56
40Recursiveestimationmethods//58
4.1.Introduction//58
4.2.Deterministicmodels//58
4.2.1.Least-squaresmethod//58
4.2.2.Projectionmethod//62
4.2.3.Modifiedprojectionmethod//62
4.2.4.Modifiedprojectionmethodforpredictionmodel//64
4.2.5.Modifiedleast-squaresmethodforpredictionmodel//64
4.3.Stochasticmodels//65
4.3.1.Least-squaresmethod//65
4.3.2.Bias-eliminatedleast-squaresmethod//65
4.3.3.Kalmanfiltermethod//66
4.3.4.Stochasticapproximationmethod//67
4.3.5.Instrumentalvariablesmethod//67
4.3.6.Extendedleast-squaresmethod//68
4.3.7.Maximumlikelihoodmethod//68
4.3.8.ExtendedKalmanpredictor//69
4.3.9.Second-orderfilter//71
4.4.Boundednoisemodels//72
4.4.1.Least-squaresmethod//72
4.4.2.Least-squaresmethodforpredictionmodel//73
4.4.3.EW-RLSalgorithm//74
4.4.4.MVSAalgorithm//74
4.4.5.Fixeddeadzonemethod//75
4.4.6.Projectionmethodwithdeadzone//76
4.5.Recursiveestimationoftheorderandparameters//78
4.5.1.Introduction//78
4.5.2.Preliminaryassumptions//79
4.5.3.Recursiveestimationofthedegreesandcoefficients//80
4.5.4.Recursivealgorithmforthesimultaneousdegreesandparametersestimation//83
4.6.Modeldelayestimation//86
50Time-variantsystemidentification//89
5.1.Introduction//89
5.2.Weightedleast-squaresmethod//90
5.3.Forgettingfactorandwindupinestimation//90
5.4.Modificationsofrecursiveleast-squaresmethod//92
5.4.1.Investigationofpersistentexcitationcondition//92
5.4.2.Adaptationtonoise//94
5.4.3.Robustestimation//95
60Closed-loopsystemidentification//97
6.1.Introduction//97
6.2.Exampleoffirst-orderinertiasystem//97
