bootstrap techniques signal processing di zoubir abdelhak (37 risultati)

Condizione: Very Good. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects.

hardcover. Condizione: As New. Cambridge University Press; Cambridge, 2004. Hardcover. A Near Fine, binding sturdy and intact, some handling/scuff marks to boards, bit of edge/corner wear, couple of small faint red scuff marks top text block edge, without Dust wrapper. A nice, clean and unmarked copy. 8vo[octavo or approx. 6 x 9 inches], 217pp., references, indexed. We pack securely and ship daily with delivery confirmation on every book. The picture on the listing page is of the actual book for sale. Additional Scan(s) are available for any item, please inquire.Please note: Oversized books/sets MAY require additional postage then what is quoted for 2.2lb book.

Condizione: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,700grams, ISBN:9780521831277.

Hardcover. Condizione: Like New. First Edition. A firm and square hardback with sharp corners and strong joints, just showing a few very minor rubs. Hence a non-text page has a small 'damaged' stamp. Despite such this book is actually in nearly new condition and appears unread. Thus the contents are crisp, fresh and tight. Also, no pen-marks and not from a library so no such stamps or labels. Now offered for sale at a very sensible price.

Condizione: New. SUPER FAST SHIPPING.

Condizione: New.

Paperback. Condizione: new. Paperback. The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering. The statistical bootstrap is a powerful tool in signal processing. This book covers the foundations of the bootstrap, its properties, its strengths, its limitations and model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condizione: New. In.

PF. Condizione: New.

Paperback. Condizione: Wie neu. 232 S.; Ill. Like new. Shrink wrapped. Sprache: Englisch Gewicht in Gramm: 485.

Condizione: New. pp. 232.

Paperback. Condizione: new. Paperback. The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering. The statistical bootstrap is a powerful tool in signal processing. This book covers the foundations of the bootstrap, its properties, its strengths, its limitations and model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condizione: New. SUPER FAST SHIPPING.

Condizione: New.

Condizione: New.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering.

Hardcover. Condizione: Like New. Like New. book.

Condizione: As New. Unread book in perfect condition.

Condizione: New. In.

Condizione: New.

Hardcover. Condizione: new. Hardcover. The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths, and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering, and automotive engineering. The statistical bootstrap is a powerful tool in signal processing. This book covers the foundations of the bootstrap, its properties, its strengths, its limitations and model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condizione: As New. Unread book in perfect condition.

Hardcover. Condizione: new. Hardcover. The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths, and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering, and automotive engineering. The statistical bootstrap is a powerful tool in signal processing. This book covers the foundations of the bootstrap, its properties, its strengths, its limitations and model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering.

orig.boards Minor rubbing. Slight binding corner bump. VG. Textual graphs & tables. 25x17cm, xiv,217 pp Contents: Introduction; The bootstrap principle; Signal detection with the bootstrap; Bootstrap model selection; Real data applications. ["This book is about the foundations of the bootstrap, a powerful tool in signal processing, and its properties, strengths, and limitations. Focused on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection, the theory developed by the authors is supported by practical examples written in MATLAB. Aimed at graduate students and engineers, the book includes applications to problems in radar and sonar, biomedical engineering, and automotive engineering." - Publisher's description] Minor rubbing. Slight binding corner bump. VG.

Paperback. Condizione: Brand New. 1st edition. 231 pages. 9.53x6.69x0.55 inches. In Stock. This item is printed on demand.

Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 410.

Condizione: New. Print on Demand pp. 232 67:B&W 6.69 x 9.61 in or 244 x 170 mm (Pinched Crown) Perfect Bound on White w/Gloss Lam.

Condizione: New. PRINT ON DEMAND pp. 232.

Paperback. Condizione: new. Paperback. The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering. The statistical bootstrap is a powerful tool in signal processing. This book covers the foundations of the bootstrap, its properties, its strengths, its limitations and model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.