Matrix Mathematics: A Second Course in Linear Algebra | Agenda Bookshop Skip to content
Online orders placed from 19/12 onward will not arrive in time for Christmas.
Online orders placed from 19/12 onward will not arrive in time for Christmas.
A01=Roger A. Horn
A01=Stephan Ramon Garcia
Age Group_Uncategorized
Age Group_Uncategorized
Author_Roger A. Horn
Author_Stephan Ramon Garcia
automatic-update
Category1=Non-Fiction
Category=PBF
COP=United Kingdom
Delivery_Delivery within 10-20 working days
Language_English
PA=In stock
Price_€50 to €100
PS=Active
softlaunch

Matrix Mathematics: A Second Course in Linear Algebra

English

By (author): Roger A. Horn Stephan Ramon Garcia

Using a modern matrix-based approach, this rigorous second course in linear algebra helps upper-level undergraduates in mathematics, data science, and the physical sciences transition from basic theory to advanced topics and applications. Its clarity of exposition together with many illustrations, 900+ exercises, and 350 conceptual and numerical examples aid the student's understanding. Concise chapters promote a focused progression through essential ideas. Topics are derived and discussed in detail, including the singular value decomposition, Jordan canonical form, spectral theorem, QR factorization, normal matrices, Hermitian matrices, and positive definite matrices. Each chapter ends with a bullet list summarizing important concepts. New to this edition are chapters on matrix norms and positive matrices, many new sections on topics including interpolation and LU factorization, 300+ more problems, many new examples, and color-enhanced figures. Prerequisites include a first course in linear algebra and basic calculus sequence. Instructor's resources are available. See more
Current price €64.59
Original price €67.99
Save 5%
A01=Roger A. HornA01=Stephan Ramon GarciaAge Group_UncategorizedAuthor_Roger A. HornAuthor_Stephan Ramon Garciaautomatic-updateCategory1=Non-FictionCategory=PBFCOP=United KingdomDelivery_Delivery within 10-20 working daysLanguage_EnglishPA=In stockPrice_€50 to €100PS=Activesoftlaunch
Delivery/Collection within 10-20 working days
Product Details
  • Weight: 1120g
  • Dimensions: 183 x 259mm
  • Publication Date: 25 May 2023
  • Publisher: Cambridge University Press
  • Publication City/Country: United Kingdom
  • Language: English
  • ISBN13: 9781108837101

About Roger A. HornStephan Ramon Garcia

Stephan Ramon Garcia is W .M. Keck Distinguished Service Professor and Chair of the Department of Mathematics and Statistics at Pomona College. He is the author of five books and over 100 research articles in operator theory complex analysis matrix analysis number theory discrete geometry and combinatorics. He has served on the editorial boards of the Proceedings of the American Mathematical Society Notices of the American Mathematical Society Involve and The American Mathematical Monthly. He received six teaching awards from three different institutions and is a fellow of the American Mathematical Society which has awarded him the inaugural Dolciani Prize for Excellence in Research. Roger A. Horn was Professor and Chair of the Department of Mathematical Sciences at the Johns Hopkins University and Research Professor of Mathematics at the University of Utah until his retirement in 2015. His publications include Matrix Analysis 2nd edition (Cambridge 2012) and Topics in Matrix Analysis (with Charles R. Johnson Cambridge 1991) as well as more than 100 research articles in matrix analysis statistics health services research complex variables probability differential geometry and analytic number theory. He was the editor of The American Mathematical Monthly and has served on the editorial boards of the SIAM Journal of Matrix Analysis Linear Algebra and its Applications and the Electronic Journal of Linear Algebra.

Customer Reviews

Be the first to write a review
0%
(0)
0%
(0)
0%
(0)
0%
(0)
0%
(0)
We use cookies to ensure that we give you the best experience on our website. If you continue we'll assume that you are understand this. Learn more
Accept