Introduction to Sparse Matrices In Scilab - Projects

dnaupddneupddsaupddsaupdznaupdzneupdcompute approximations to a few eigenpairs ofa real linear operatorcompute the converged approximations to eigenvaluesof Az = λBz, approximations to a few eigenpairsof a real linear operatorcompute approximations to a few eigenpairs of a real andsymmetric linear operatorcompute approximations to the converged approximations toeigenvalues of Az = λBzcompute a few eigenpairs of a complex linear operatorwith respect to a semi-inner product defined by ahermitian positive semi-definite real matrix B.compute approximations to the converged approximations toeigenvalues of Az = λBzFigure 10 – Functions from the Arnoldi Package.– Single and Double Precision Real Arithmetic Versions for Symmetric,Non-symmetric,– Standard or Generalized Problems.– Single and Double Precision Complex Arithmetic Versions for Standardor Generalized Problems.– Routines for Banded Matrices - Standard or Generalized Problems.– Routines for The Singular Value Decomposition.– Example driver routines that may be used as templates to implementnumerous Shift-Invert strategies for all problem types, data types andprecision.10 The Matrix Market moduleThe Matrix Market (MM) exchange formats provide a simple mechanismto facilitate the exchange of matrix data. In particular, the objective hasbeen to define a minimal base ASCII file format which can be very easilyexplained and parsed, but can easily adapted to applications with a morerigid structure, or extended to related data objects. The MM exchange formatfor matrices is really a collection of affiliated formats which share design24