Temlyakov (55 resultados)

Hardcover. Condición: Like New. First Edition. Firm and square with strong joints, just showing a few very minor rubs and bumps. Hence a non-text page is stamped 'damaged'. Despite such this book is actually in nearly new condition. Thus it looks and feels unread with contents that are crisp, fresh and tight. Size: 250mm x 180mm. Pages: xvi, 534. Fully indexed. This self-contained, systematic treatment of multivariate approximation begins with classical linear approximation, and moves on to contemporary nonlinear approximation. It covers substantial new developments in the linear approximation theory of classes with mixed smoothness, and shows how it is directly related to deep problems in other areas of mathematics.…

Hardcover. Condición: New. Estado de la sobrecubierta: No dust jacket, as issued. First Edition. New York: Cambridge University Press, 2011. BRAND NEW in PERFECT condition. Sharp corners. NO rubbing. NO fading. Square and tight. NO creases. NO owner's name or bookplate. Crisp, clean and unmarked - obviously never read. Cambridge Monographs on Applied and Computational Mathematics. Bound in the original gray boards, stamped in bright green, white and black. From the rear cover: "This first book on greedy approximation gives a systematic presentation of the fundamental results. It also contains an introduction to two hot topics in numerical mathematics: learning theory and compressed sensing. Nonlinear approximation is becoming increasingly important, especially since two types are frequently employed in applications: adaptive methods are used in PDE solvers, while m-term approximation is used in image/signal/data processing, as well as in the design of neural networks. The fundamental question of nonlinear approximation is how to devise good constructive methods (algorithms) and recent results have established that greedy type algorithms may be the solution. The author has drawn on his own teaching experience to write a book ideally suited to graduate courses. The reader does not require a broad background to understand the material. Important open problems are included to give students and professionals alike ideas for further research.". First Edition. Oversize Hardcover. New/No dust jacket, as issued. 8vo. xiv, 418pp. Great Packaging, Fast Shipping. …

paperback. Condición: Good. Crease on cover and a few pages*.

Trade Paperback. Condición: Good. No Dust Jacket. First U.S. Edition. An ex-library copy in original paper covers. The usual ex-libris markings, clean within. The binding is sound, and there is little wear to the covers. Book.

Condición: New.

Hardback. Condición: New. This first book on greedy approximation gives a systematic presentation of the fundamental results. It also contains an introduction to two hot topics in numerical mathematics: learning theory and compressed sensing. Nonlinear approximation is becoming increasingly important, especially since two types are frequently employed in applications: adaptive methods are used in PDE solvers, while m-term approximation is used in image/signal/data processing, as well as in the design of neural networks. The fundamental question of nonlinear approximation is how to devise good constructive methods (algorithms) and recent results have established that greedy type algorithms may be the solution. The author has drawn on his own teaching experience to write a book ideally suited to graduate courses. The reader does not require a broad background to understand the material. Important open problems are included to give students and professionals alike ideas for further research.…

Hardcover. Condición: Very Good. Unread. In stock ready to dispatch from the UK.

Hardcover. Condición: New. In stock ready to dispatch from the UK.

Condición: As New. Unread book in perfect condition.

Condición: New.

Hardback. Vladimir Temlyakov (University of South Carolina), Cambridge University Press. This first book on greedy approximation gives a systematic presentation of the fundamental results. It also contains an introduction to two hot topics in numerical mathematics: learning theory and compressed sensing. Nonlinear approximation is becoming increasingly important, especially since two types are frequently employed in applications: adaptive methods are used in PDE solvers, while m-term approximation is used in image/signal/data processing, as well as in the design of neural networks. The fundamental question of nonlinear approximation is how to devise good constructive methods (algorithms) and recent results have established that greedy type algorithms may be the solution. The author has drawn on his own teaching experience to write a book ideally suited to graduate courses. The reader does not require a broad background to understand the material. Important open problems are included to give students and professionals alike ideas for further research. Hardback.…

Condición: Very Good.

Condición: New.

Condición: New. In English.

Condición: New. pp. 229.

Condición: As New. Unread book in perfect condition.

Paperback. Condición: Brand New. 232 pages. 9.45x6.61x0.51 inches. In Stock.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: New.

Condición: New. In English.

Condición: New. Provides the theoretical foundations for algorithms widely used in numerical mathematics. Includes classical results, as well as the latest advances. Series: Cambridge Monographs on Applied and Computational Mathematics. Num Pages: 432 pages, illustrations. BIC Classification: PBKS. Category: (U) Tertiary Education (US: College). Dimension: 160 x 231 x 26. Weight in Grams: 754. . 2011. hardcover. . . . . …

Condición: New.

Hardback. Condición: New. This first book on greedy approximation gives a systematic presentation of the fundamental results. It also contains an introduction to two hot topics in numerical mathematics: learning theory and compressed sensing. Nonlinear approximation is becoming increasingly important, especially since two types are frequently employed in applications: adaptive methods are used in PDE solvers, while m-term approximation is used in image/signal/data processing, as well as in the design of neural networks. The fundamental question of nonlinear approximation is how to devise good constructive methods (algorithms) and recent results have established that greedy type algorithms may be the solution. The author has drawn on his own teaching experience to write a book ideally suited to graduate courses. The reader does not require a broad background to understand the material. Important open problems are included to give students and professionals alike ideas for further research.…

Condición: New.

Hardcover. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condición: New.

Condición: New. pp. xiv + 418 Index.

Condición: New. Provides the theoretical foundations for algorithms widely used in numerical mathematics. Includes classical results, as well as the latest advances. Series: Cambridge Monographs on Applied and Computational Mathematics. Num Pages: 432 pages, illustrations. BIC Classification: PBKS. Category: (U) Tertiary Education (US: College). Dimension: 160 x 231 x 26. Weight in Grams: 754. . 2011. hardcover. . . . . Books ship from the US and Ireland. …