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[null,"1.","Record Nr.",null,"UNINA9911007277703321"]
[null,null,"Autore",null,"Goodwin Graham C (Graham Clifford), <1945->"]
[null,null,"Titolo",null,"Adaptive Filtering Prediction and Control"]
[null,null,"Pubbl/distr/stampa",null,"Newburyport, : Dover Publications, 2014"]
[null,null,"ISBN",null,"0-486-13772-4"]
[{"$nulls":4},"1-62870-072-6"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (1123 p.)"]
[null,null,"Collana",null,"Dover Books on Electrical Engineering"]
[null,null,"Disciplina",null,"003/.83"]
[null,null,"Soggetti",null,"Discrete-time systems"]
[{"$nulls":4},"Filters (Mathematics)"]
[{"$nulls":4},"Prediction theory"]
[{"$nulls":4},"Control theory"]
[{"$nulls":4},"Civil & Environmental Engineering"]
[{"$nulls":4},"Engineering & Applied Sciences"]
[{"$nulls":4},"Operations Research"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,"Nota di contenuto",null,"Cover; Title Page; Copyright Page; Table of Contents; Preface; 1 Introduction To Adaptive Techniques; 1.1 Filtering; 1.2 Prediction; 1.3 Control; Part I: Deterministic Systems; 2 Models for Deterministic Dynamical Systems; 2.1 Introduction; 2.2 State-Space Models; 2.2.1 General; 2.2.2 Controllable State-Space Models; 2.2.3 Observable State-Space Models; 2.2.4 Minimal State-Space Models; 2.3 Difference Operator Representations; 2.3.1 General; 2.3.2 Right Difference Operator Representations; 2.3.3 Left Difference Operator Representations; 2.3.4 Deterministic Autoregressive Moving-Average Models"]
[{"$nulls":4},"2.3.5 Irreducible Difference Operator Representations2.4 Models for Bilinear Systems; 3 Parameter Estimation for Deterministic Systems; 3.1 Introduction; 3.2 On-Line Estimation Schemes; 3.3 Equation Error Methods for Deterministic Systems; 3.4 Parameter Convergence; 3.4.1 The Orthogonalized Projection Algorithm; 3.4.2 The Least-Squares Algorithm; 3.4.3 The Projection Algorithm; 3.4.4 Persistent Excitation; 3.5 Output Error Methods; 3.6 Parameter Estimation with Bounded Noise; 3.7 Constrained Parameter Estimation; 3.8 Parameter Estimation for Multi-output Systems; 3.9 Concluding Remarks"]
[{"$nulls":4},"4 Deterministic Adaptive Prediction4.1 Introduction; 4.2 Predictor Structures; 4.2.1 Prediction with Known Models; 4.2.2 Restricted Complexity Predictors; 4.3 Adaptive Prediction; 4.3.1 Direct Adaptive Prediction; 4.3.2 Indirect Adaptive Prediction; 4.4 Concluding Remarks; 5 Control of Linear Deterministic Systems; 5.1 Introduction; 5.2 Minimum Prediction Error Controllers; 5.2.1 One-Step-Ahead Control (The SISO Case); 5.2.2 Model Reference Control (The SISO Case); 5.2.3 One-Step-Ahead Design for Multi-input Multi-output Systems; 5.2.4 Robustness Considerations"]
[{"$nulls":4},"5.3 Closed-Loop Pole Assignment5.3.1 Introduction; 5.3.2 The Pole Assignment Algorithm (Difference Operator Formulation); 5.3.3 Rapprochement with State- Variable Feedback; 5.3.4 Rapprochement with Minimum Prediction Error Control; 5.3.5 The Internal Model Principle; 5.3.6 Some Design Considerations; 5.4 An Illustrative Example; 6 Adaptive Control Of Linear Deterministic Systems; 6.1 Introduction; 6.2 The Key Technical Lemma; 6.3 Minimum Prediction Error Adaptive Controllers (Direct Approach); 6.3.1 One-Step-Ahead Adaptive Control (The SISO Case); 6.3.2 Model Reference Adaptive Control"]
[{"$nulls":4},"6.3.3 One-Step-Ahead Adaptive Controllers for Multi-input Multi-output Systems6.4 Minimum Prediction Error Adaptive Controllers (Indirect Approach); 6.5 Adaptive Algorithms for Closed-Loop Pole Assignment; 6.6 Adaptive Control of Nonlinear Systems; 6.7 Adaptive Control of Time-Varying Systems; 6.8 Some Implementation Considerations; Part II: Stochastic Systems; 7 Optimal Filtering and Prediction; 7.1 Introduction; 7.2 Stochastic State-Space Models; 7.3 Linear Optimal Filtering and Prediction; 7.3.1 The Kalman Filter; 7.3.2 Fixed-Lag Smoothing; 7.3.3 Fixed-Point Smoothing"]
[{"$nulls":4},"7.3.4 Optimal Prediction"]
[null,null,null,"Sommario/riassunto","This unified survey of the theory of adaptive filtering, prediction, and control focuses on linear discrete-time systems and explores the natural extensions to nonlinear systems. In keeping with the importance of computers to practical applications, the authors emphasize discrete-time systems. Their approach summarizes the theoretical and practical aspects of a large class of adaptive algorithms.Ideal for advanced undergraduate and graduate classes, this treatment consists of two parts. The first section concerns deterministic systems, covering models, parameter estimation, and adaptive predic"]