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Studi GiuridiciitaSocioculturale Scseng32123Beloff, Max75548Imperial sunset /Max BeloffLondon :Methuen & Co,1969volumi ,25 cmVol. 1. :Britain's liberal empire, 1897-1921. -XII, 387 p. : c. geogr.Gran BretagnaLiberalismoStoria1897-1921991004383936807536Imperial sunset4386105UNISALENTO05717nam 22007573u 450 991100727770332120230803195245.00-486-13772-41-62870-072-6(CKB)2670000000525512(EBL)1894528(SSID)ssj0001082436(PQKBManifestationID)12450737(PQKBTitleCode)TC0001082436(PQKBWorkID)11100779(PQKB)10227752(MiAaPQ)EBC1894528(Au-PeEL)EBL1894528(CaONFJC)MIL618864(OCoLC)765641472(EXLCZ)99267000000052551220141222d2014|||| u|| |engur|n|---|||||txtccrAdaptive Filtering Prediction and Control1st ed.Newburyport Dover Publications20141 online resource (1123 p.)Dover Books on Electrical EngineeringDescription based upon print version of record.0-486-46932-8 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 Models2.3.5 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 Remarks4 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 Considerations5.3 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 Control6.3.3 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 Smoothing7.3.4 Optimal PredictionThis 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 predicDover Books on Electrical EngineeringDiscrete-time systemsFilters (Mathematics)Prediction theoryControl theoryCivil & Environmental EngineeringHILCCEngineering & Applied SciencesHILCCOperations ResearchHILCCDiscrete-time systems.Filters (Mathematics)Prediction theory.Control theory.Civil & Environmental EngineeringEngineering & Applied SciencesOperations Research003/.83Goodwin Graham C(Graham Clifford),1945-13807Sin Kwai Sang1825188AU-PeELAU-PeELAU-PeELBOOK9911007277703321Adaptive Filtering Prediction and Control4392703UNINA