9780471708582 - Optimal State Estimation: Kalman, H Infinity, And Nonlinear Approaches di Simon, Dan (25 risultati)

hardcover. Condizione: Good. 1st Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Condizione: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

Condizione: New.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: new.

Condizione: As New. Unread book in perfect condition.

HARDCOVER. Condizione: New.

Condizione: New. In.

Condizione: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

Condizione: NEW.

Condizione: New. pp. xxvi + 526 Illus.

Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.

Condizione: New. This is a book that is clear and lucid in its presentation of the technically difficult area of state estimation. The bottom-up approach taken in this text lays the foundation one block at a time until the reader has a firm grasp of optimal filtering. Num Pages: 552 pages, Illustrations. BIC Classification: PBT; TJ. Category: (P) Professional & Vocational. Dimension: 260 x 188 x 28. Weight in Grams: 1150. . 2006. 1st Edition. Hardcover. . . . .

Hardcover. Condizione: Brand New. 1st edition. 552 pages. 10.00x7.25x1.00 inches. In Stock.

Hardback. Condizione: New. A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering. While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning: Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimationSimple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practiceMATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering. Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.

Condizione: New. pp. xxvi + 526.

Condizione: New. DAN SIMON, PhD, is an Associate Professor at Cleveland State University. Prior to this appointment, Dr. Simon spent fourteen years working for such firms as Boeing, TRW, and several smaller companies.A bottom-up approach that enables readers to master a.

Hardcover. Condizione: Brand New. 1st edition. 552 pages. 10.00x7.25x1.00 inches. In Stock.

Buch. Condizione: Neu. Neuware - A bottom-up approach that enables readers to master and apply the latest techniques in state estimationThis book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering.While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning:\* Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimation\* Simple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practice\* MATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parametersArmed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H filtering.Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. A solutions manual is available for instructors.With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.

Condizione: New. This is a book that is clear and lucid in its presentation of the technically difficult area of state estimation. The bottom-up approach taken in this text lays the foundation one block at a time until the reader has a firm grasp of optimal filtering. Num Pages: 552 pages, Illustrations. BIC Classification: PBT; TJ. Category: (P) Professional & Vocational. Dimension: 260 x 188 x 28. Weight in Grams: 1150. . 2006. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Buch. Condizione: Neu. Optimal State Estimation | Kalman, H Infinity, and Nonlinear Approaches | Dan Simon | Buch | XXVI | Englisch | 2006 | John Wiley & Sons | EAN 9780471708582 | Verantwortliche Person für die EU: Wiley-VCH GmbH, Boschstr. 12, 69469 Weinheim, product-safety[at]wiley[dot]com | Anbieter: preigu.

Hardback. Condizione: New. A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering. While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning: Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimationSimple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practiceMATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering. Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.

Hardcover. Condizione: new. Hardcover. A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering. While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning: Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimationSimple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practiceMATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering. Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries. This is a book that is clear and lucid in its presentation of the technically difficult area of state estimation. The bottom-up approach taken in this text lays the foundation one block at a time until the reader has a firm grasp of optimal filtering. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.