Liu Joseph W H (21 results)

Soft cover. Condition: Near Fine. Previous owner's embossed mark on the first page. Otherwise spotless and completely free of wear or damage inside and out. It will be bubble-wrapped and carefully packed in a sturdy box to ensure safe transit. This issue includes: "History of Pressure Pattern Navigation" by John C. Bellamy; "The Early History of Airborn Doppler Systems" by William J. Tull; "Fixing the GPS Bad Attitude: Modeling GPS Satellite Yaw during Eclipse Seasons" by Yoaz E. Bar-Sever, William I. Bertiger, Edgar (Ab) S. Davis, and Joseph A. Anselmi; "Characterization of Phase and Multipath Errors for an Aircraft GPS Antenna" by C.D. Hardwick and Jeffrey Liu; "Evaluation of a Perspective-View Cockpit Display for General Aviation Using GPS" by Andrew K. Barrows, Per Enge, Bradford W. Parkinson and J. David Powell; "RAIM Availability of GPS Augmented with Loran-C and Barometric Altimeter for Use in Nonprecision Approach" by Jay Weitzen, James V. Carroll, and H. James Rome; and "Relative Targeting with Differential GPS and Associated Error Mechanisms" by Michael P. Fikes.

Hardcover. Condition: Good. xii, 324pp. Grey cloth-covered boards; gilt titles on red printed labels on front and spine. 8vo. Sun-faded spine, rubbed extremities, annotations and soiling to boards; shelf number label on spine. Text block edges just starting to tan. Lender's stamps, security device and markings on endpapers and copyright pages, rippling to first few page. Otherwise, internally neat, clean, bright and tight.

Hardcover. Condition: Good. Ex library copy.

Hardcover. Condition: As New. Still shrinkwrapped; The IMA Volumes In Mathematics And Its Applications; 8vo 8" - 9" tall; 245 pages.

Condition: Very Good. 324 pp., Hardcover, bookplate to front free endpaper else text clean & binding tight. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.

Condition: New.

Paperback. Condition: new. Paperback. This book looks at graph theory as it connects to linear algebra, parallel computing, data structures, geometry, and both numerical and discrete algorithms. This book will be a resource for the researcher or advanced student of either graphs or sparse matrices; it will be useful to mathematicians, numerical analysis and theoretical computer scientists alike. When reality is modeled by computation, matrices are often the connection between the continuous physical world and the finite algorithmic one. Usually, the more detailed the model, the bigger the matrix, the better the answer, however, efficiency demands that every possible advantage be exploited. The articles in this volume are based on recent research on sparse matrix computations. This volume looks at graph theory as it connects to linear algebra, parallel computing, data structures, geometry, and both numerical and discrete algorithms. The articles are grouped into three general categories: graph models of symmetric matrices and factorizations, graph models of algorithms on nonsymmetric matrices, and parallel sparse matrix algorithms. This book will be a resource for the researcher or advanced student of either graphs or sparse matrices; it will be useful to mathematicians, numerical analysts and theoretical computer scientists alike. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New.

Condition: Very Good. Book is undamaged. Probably very lightly used. Has inscriptions to the inside page and cover, otherwise rest of content is in excellent condition.

Condition: As New. Unread book in perfect condition.

Condition: New. In.

245 pp. with Figures, 0387941312 Sprache: Englisch Gewicht in Gramm: 540 Groß 8°, Original-Pappband (Hardcover), Bibliotheks-Exemplar (ordnungsgemäß entwidmet) mit Rückenschild, Stempel auf Titel, insgesamt gutes und innen sauberes Exemplar, (library copy in good condition),

Condition: New. pp. 264.

Paperback. Condition: Brand New. reprint edition. 245 pages. 9.25x6.10x0.60 inches. In Stock.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This IMA Volume in Mathematics and its Appllcations GRAPH THEORY AND SPARSE MATRIX COMPUTATION is based on the proceedings of a workshop that was an integraI part of the 1991- 92 IMA program on 'Applied Linear AIgebra.' The purpose of the workshop was to bring together people who work in sparse matrix computation with those who conduct research in applied graph theory and grl:l,ph algorithms, in order to foster active cross-fertilization. We are grateful to Richard Brualdi, George Cybenko, Alan Geo~ge, Gene Golub, Mitchell Luskin, and Paul Van Dooren for planning and implementing the year-Iong program. We espeeially thank Alan George, John R. Gilbert, and Joseph W.H. Liu for organizing this workshop and editing the proceedings. The finaneial support of the National Science Foundation made the workshop possible. A vner Friedman Willard Miller. Jr. PREFACE When reality is modeled by computation, linear algebra is often the con nec tiori between the continuous physical world and the finite algorithmic one. Usually, the more detailed the model, the bigger the matrix, the better the answer. Efficiency demands that every possible advantage be exploited: sparse structure, advanced com puter architectures, efficient algorithms. Therefore sparse matrix computation knits together threads from linear algebra, parallei computing, data struetures, geometry, and both numerieal and discrete algorithms.

Paperback. Condition: new. Paperback. This book looks at graph theory as it connects to linear algebra, parallel computing, data structures, geometry, and both numerical and discrete algorithms. This book will be a resource for the researcher or advanced student of either graphs or sparse matrices; it will be useful to mathematicians, numerical analysis and theoretical computer scientists alike. When reality is modeled by computation, matrices are often the connection between the continuous physical world and the finite algorithmic one. Usually, the more detailed the model, the bigger the matrix, the better the answer, however, efficiency demands that every possible advantage be exploited. The articles in this volume are based on recent research on sparse matrix computations. This volume looks at graph theory as it connects to linear algebra, parallel computing, data structures, geometry, and both numerical and discrete algorithms. The articles are grouped into three general categories: graph models of symmetric matrices and factorizations, graph models of algorithms on nonsymmetric matrices, and parallel sparse matrix algorithms. This book will be a resource for the researcher or advanced student of either graphs or sparse matrices; it will be useful to mathematicians, numerical analysts and theoretical computer scientists alike. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This IMA Volume in Mathematics and its Appllcations GRAPH THEORY AND SPARSE MATRIX COMPUTATION is based on the proceedings of a workshop that was an integraI part of the 1991- 92 IMA program on 'Applied Linear AIgebra.' The purpose of the workshop was to bring together people who work in sparse matrix computation with those who conduct research in applied graph theory and grl:l,ph algorithms, in order to foster active cross-fertilization. We are grateful to Richard Brualdi, George Cybenko, Alan Geo~ge, Gene Golub, Mitchell Luskin, and Paul Van Dooren for planning and implementing the year-Iong program. We espeeially thank Alan George, John R. Gilbert, and Joseph W.H. Liu for organizing this workshop and editing the proceedings. The finaneial support of the National Science Foundation made the workshop possible. A vner Friedman Willard Miller. Jr. PREFACE When reality is modeled by computation, linear algebra is often the con nec tiori between the continuous physical world and the finite algorithmic one. Usually, the more detailed the model, the bigger the matrix, the better the answer. Efficiency demands that every possible advantage be exploited: sparse structure, advanced com puter architectures, efficient algorithms. Therefore sparse matrix computation knits together threads from linear algebra, parallei computing, data struetures, geometry, and both numerieal and discrete algorithms. 264 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book looks at graph theory as it connects to linear algebra, parallel computing, data structures, geometry, and both numerical and discrete algorithms. This book will be a resource for the researcher or advanced student of either graphs or sparse matri.

Condition: New. Print on Demand pp. 264 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

Condition: New. PRINT ON DEMAND pp. 264.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This IMA Volume in Mathematics and its Appllcations GRAPH THEORY AND SPARSE MATRIX COMPUTATION is based on the proceedings of a workshop that was an integraI part of the 1991- 92 IMA program on 'Applied Linear AIgebra.' The purpose of the workshop was to bring together people who work in sparse matrix computation with those who conduct research in applied graph theory and grl:l,ph algorithms, in order to foster active cross-fertilization. We are grateful to Richard Brualdi, George Cybenko, Alan Geo~ge, Gene Golub, Mitchell Luskin, and Paul Van Dooren for planning and implementing the year-Iong program. We espeeially thank Alan George, John R. Gilbert, and Joseph W.H. Liu for organizing this workshop and editing the proceedings. The finaneial support of the National Science Foundation made the workshop possible. A vner Friedman Willard Miller. Jr. PREFACE When reality is modeled by computation, linear algebra is often the con nec tiori between the continuous physical world and the finite algorithmic one. Usually, the more detailed the model, the bigger the matrix, the better the answer. Efficiency demands that every possible advantage be exploited: sparse structure, advanced com puter architectures, efficient algorithms. Therefore sparse matrix computation knits together threads from linear algebra, parallei computing, data struetures, geometry, and both numerieal and discrete algorithms.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 264 pp. Englisch.