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1. |
Record Nr. |
UNISALENTO991003353299707536 |
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Autore |
Beals, Ralph L. |
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Titolo |
Introduzione all'antropologia culturale / Ralph L. Beals, Harry Hoijer |
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Pubbl/distr/stampa |
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Bologna : Il Mulino, c1987 |
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ISBN |
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Descrizione fisica |
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Collana |
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Altri autori (Persone) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910818728503321 |
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Autore |
Dong Hongli <1977-> |
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Titolo |
Filtering, control, and fault detection with randomly occurring incomplete information / / Hongli Dong, Zidong Wang, Huijun Gao |
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Pubbl/distr/stampa |
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Chichester, West Sussex, U.K., : Wiley, c2013 |
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ISBN |
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9781118650974 |
1118650972 |
9781118650981 |
1118650980 |
9781118650967 |
1118650964 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (283 p.) |
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Altri autori (Persone) |
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WangZidong <1966-> |
GaoHuijun |
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Disciplina |
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Soggetti |
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Automatic control |
Electric filters, Digital |
Fault tolerance (Engineering) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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FILTERING, CONTROL AND FAULT DETECTION WITH RANDOMLY OCCURRING INCOMPLETE INFORMATION; Contents; Preface; Acknowledgments; List of Abbreviations; List of Notations; 1 Introduction; 1.1 Background, Motivations, and Research Problems; 1.1.1 Randomly Occurring Incomplete Information; 1.1.2 The Analysis and Synthesis of Nonlinear Stochastic Systems; 1.1.3 Distributed Filtering over Sensor Networks; 1.2 Outline; 2 Variance-Constrained Finite-Horizon Filtering and Control with Saturations; 2.1 Problem Formulation for Finite-Horizon Filter Design; 2.2 Analysis of H and Covariance Performances |
2.2.1 H Performance2.2.2 Variance Analysis; 2.3 Robust Finite-Horizon Filter Design; 2.4 Robust H Finite-Horizon Control with Sensor and Actuator Saturations; 2.4.1 Problem Formulation; 2.4.2 Main Results; 2.5 Illustrative Examples; 2.5.1 Example 1; 2.5.2 Example 2; 2.6 Summary; 3 Filtering and Control with Stochastic Delays and Missing Measurements; 3.1 Problem Formulation for Robust Filter Design; 3.2 Robust H Filtering Performance Analysis; 3.3 Robust H Filter Design; 3.4 Robust H Fuzzy Control; 3.4.1 Problem Formulation; 3.4.2 Performance Analysis; 3.4.3 Controller Design |
3.5 Illustrative Examples3.5.1 Example 1; 3.5.2 Example 2; 3.5.3 Example 3; 3.6 Summary; 4 Filtering and Control for Systems with Repeated Scalar Nonlinearities; 4.1 Problem Formulation for Filter Design; 4.1.1 The Physical Plant; 4.1.2 The Communication Link; 4.1.3 The Filter; 4.1.4 The Filtering Error Dynamics; 4.2 Filtering Performance Analysis; 4.3 Filter Design; 4.4 Observer-Based H Control with Multiple Packet Losses; 4.4.1 Problem Formulation; 4.4.2 Main Results; 4.5 Illustrative Examples; 4.5.1 Example 1; 4.5.2 Example 2; 4.5.3 Example 3; 4.5.4 Example 4; 4.6 Summary |
5 Filtering and Fault Detection for Markov Systems with Varying Nonlinearities5.1 Problem Formulation for Robust H° Filter Design; 5.2 Performance Analysis of Robust H° Filter; 5.3 Design of Robust H° Filters; 5.4 Fault Detection with Sensor Saturations and Randomly Varying Nonlinearities; 5.4.1 Problem Formulation; 5.4.2 Main Results; 5.5 Illustrative Examples; 5.5.1 Example 1; 5.5.2 Example 2; 5.5.3 Example 3; 5.5.4 Example 4; 5.6 Summary; 6 Quantized Fault Detection with Mixed Time-Delays and Packet Dropouts; 6.1 Problem Formulation for Fault Detection Filter Design; 6.2 Main Results |
6.3 Fuzzy-Model-Based Robust Fault Detection6.3.1 Problem Formulation; 6.3.2 Main Results; 6.4 Illustrative Examples; 6.4.1 Example 1; 6.4.2 Example 2; 6.5 Summary; 7 Distributed Filtering over Sensor Networks with Saturations; 7.1 Problem Formulation; 7.2 Main Results; 7.3 An Illustrative Example; 7.4 Summary; 8 Distributed Filtering with Quantization Errors: The Finite-Horizon Case; 8.1 Problem Formulation; 8.2 Main Results; 8.3 An Illustrative Example; 8.4 Summary; 9 Distributed Filtering for Markov Jump Nonlinear Time-Delay Systems; 9.1 Problem Formulation |
9.1.1 Deficient Statistics of Markovian Modes Transitions |
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Sommario/riassunto |
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In the context of systems and control, incomplete information refers to a dynamical system in which knowledge about the system states is limited due to the difficulties in modelling complexity in a quantitative way. The well-known types of incomplete information include parameter uncertainties and norm-bounded nonlinearities. Recently, in response to the development of network technologies, the phenomenon of randomly occurring incomplete information has |
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become more and more prevalent. Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information reflects |
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