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Abstrak :
Skripsi ini dilatarbelakangi oleh permasalahan 49-4 yang dikemukakan oleh Rajesh Pereira mengenai Teorema Perron-Frobenius pada relasi urutan total dalam buletin International Linear Algebra Society, yaitu "IMAGE". Pada skripsi ini dibahas pembuktian pernyataan sebab-akibat dari Teorema Perron-Frobenius yang menyatakan bahwa jika ada sebuah urutan total ≥ pada yang diawetkan (preserved) oleh A sedemikian sehingga ( ,≥) merupakan ruang vektor terurut, maka seluruh nilai eigen dari A adalah bilangan riil non-negatif.

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This paper was motivated by problem 49-4 from International Linear Algebra Society buletin, "IMAGE" which was proposed by Rajesh Pereira about Perron-Frobenius theorem for total orders. This paper presented the proof of Perron-Frobenius theorem which state that if there exists a total order ≥ on which is preserved by A and which makes (,≥) an ordered vector space, then all the eigenvalues of A are real and nonnegative.

Abstrak :
First published in 1985, Lanczos Algorithms for Large Symmetric Eigenvalue Computations; Vol. I: Theory presents background material, descriptions, and supporting theory relating to practical numerical algorithms for the solution of huge eigenvalue problems. This book deals with "symmetric" problems. However, in this book, "symmetric" also encompasses numerical procedures for computing singular values and vectors of real rectangular matrices and numerical procedures for computing eigenelements of nondefective complex symmetric matrices. Although preserving orthogonality has been the golden rule in linear algebra, most of the algorithms in this book conform to that rule only locally, resulting in markedly reduced memory requirements. Additionally, most of the algorithms discussed separate the eigenvalue (singular value) computations from the corresponding eigenvector (singular vector) computations. This separation prevents losses in accuracy that can occur in methods which, in order to be able to compute further into the spectrum, use successive implicit deflation by computed eigenvector or singular vector approximations. This book continues to be useful to the mathematical, scientific, and engineering communities as a reservoir of information detailing the nonclassical side of Lanczos algorithms and as a presentation of what continues to be the most efficient methods for certain types of large-scale eigenvalue computations.