Ming jun lai yang wang (11 risultati)

Original decorated wrappers. Condizione: New. No Dust Jacket. First Edition. In original shrinkwrap.; Octavo; 437 pages.

Condizione: New. 439 pp., paperback, NEW!!! - 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.

Original decorated wrappers. Condizione: New. No Dust Jacket. First Edition. In original shrinkwrap. Ew; Octavo; 437 pages.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Paperback / Softback. Condizione: Brand New. 437 pages. 10.28x7.05x1.18 inches. In Stock.

Paperback. Condizione: New. This textbook presents a special solution of underdetermined linear systems where the number of nonzero entries in the solution is very small compared to the total number of entries. This is called sparse solution. As underdetermined linear systems can be very different, the authors explain how to compute a sparse solution by many approaches.Sparse Solutions of Underdetermined Linear Systems:Contains 72 algorithms for finding sparse solutions of underdetermined linear systems and their applications for matrix completion, graph clustering, and phase retrieval.Provides a detailed explanation of these algorithms including derivations and convergence analysis.Includes exercises for each chapter to help the reader understand the material.This textbook is appropriate for graduate students in math and applied math, computer science, statistics, data science, and engineering. Advisors and postdocs will also find the book of interest.It is appropriate for the following courses: Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory. …

Condizione: As New. Unread book in perfect condition.

Condizione: New. In English.

Paperback. Condizione: New. This textbook presents a special solution of underdetermined linear systems where the number of nonzero entries in the solution is very small compared to the total number of entries. This is called sparse solution. As underdetermined linear systems can be very different, the authors explain how to compute a sparse solution by many approaches.Sparse Solutions of Underdetermined Linear Systems:Contains 72 algorithms for finding sparse solutions of underdetermined linear systems and their applications for matrix completion, graph clustering, and phase retrieval.Provides a detailed explanation of these algorithms including derivations and convergence analysis.Includes exercises for each chapter to help the reader understand the material.This textbook is appropriate for graduate students in math and applied math, computer science, statistics, data science, and engineering. Advisors and postdocs will also find the book of interest.It is appropriate for the following courses: Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory. …