This paper takes another look at the convergence analysis of the Arnoldi procedure for solving non-Hermitian eigenvalue problems. Two main viewpoints are put in contrast. The first exploits the ...

Eigenvalue problems are a cornerstone of modern applied mathematics, arising in diverse fields from quantum mechanics to structural engineering. At their heart, these problems seek scalar values and ...

Introduces linear algebra and matrices with an emphasis on applications, including methods to solve systems of linear algebraic and linear ordinary differential equations. Discusses vector space ...

Understanding and implementation of algorithms to calculate matrix decompositions such as eigenvalue/vector, LU, QR, and SVD decompositions. Applications include data-fitting, image analysis, and ...

Math 307 is a theoretical course in linear algebra, geared primarily for students majoring in mathematics, mathematics and physics, and applied mathematics. (Although everyone is welcome, if you're ...

All prerequisite courses must be passed with a grade of C- or better. For official course descriptions, please see the current CU-Boulder Catalog. MATH 3001 Analysis 1 Provides a rigorous treatment of ...

This asynchronous online bridge course is specifically designed to help students satisfy the linear algebra admissions requirements for Michigan Tech's Online MS in Applied Statistics, an innovative ...