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Računanje lastnih vrednosti brez uporabe determinant : delo diplomskega seminarja
ID Papež, Sara (Author), ID Dolžan, David (Mentor) More about this mentor... This link opens in a new window

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Abstract
V diplomski nalogi je formuliran algoritem za iskanje lastnih vrednosti in lastnih vektorjev brez uporabe determinante. Za algoritem je ključno razumevanje linearne neodvisnosti oziroma odvisnosti, zato je v delu to temeljito opisano. Definirali smo lastne vrednosti, lastne vektorje, matrični polinom, minimalni polinom matrike, minimalni polinom vektorja glede na matriko in v povezavi s temi pojmi navedli trditve, ki so nam pomagale pri konstrukciji algoritma. Postopek za iskanje lastnih vrednosti in vektorjev smo skozi delo gradili postopoma. Najprej smo ga uporabili na nedefektnih matrikah. Nato smo si pogledali še definicijo defektnih matrik, korenskih lastnih vektorjev, Jordanovo verigo korenskih lastnih vektorjev in trditve v povezavi z njimi. Skozi celotno diplomsko nalogo so nova dognanja uporabljena na primerih. Na koncu smo zapisali celoten univerzalen algoritem, ne glede na začetno matriko.

Language:Slovenian
Keywords:lastne vrednosti, lastni vektorji, minimalni polinom, minimalni polinom vektorja glede na matriko, korenski lastni vektor, Jordanova veriga korenskih lastnih vektorjev
Work type:Final seminar paper
Typology:2.11 - Undergraduate Thesis
Organization:FMF - Faculty of Mathematics and Physics
Year:2022
PID:20.500.12556/RUL-138317 This link opens in a new window
UDC:512
COBISS.SI-ID:116135171 This link opens in a new window
Publication date in RUL:15.07.2022
Views:826
Downloads:79
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Secondary language

Language:English
Title:Computing eigenvalues without determinants
Abstract:
In this bachelor thesis we formulate the algorithm for finding eigenvalues and eigenvectors without the use of determinant. For the algorithm to work, the understanding of linear independance and dependance is crucial, that is why we chose to present these two principles in more detail. We defined eigenvalues, eigenvectors, matrix polynomial, minimal polynomial of the matrix, and minimal polynomial of a vector with respect to matrix. These definitions and theorems helped us to construct our algorithm. We built our method step-by-step through our bachelor thesis. First, we used it on non defective matrices. Then we defined defective matrices, generalized vectors and Jordan chain of generalized eigenvectors. Throughout the thesis, examples are used to show what we have discovered till then. In the end, we formulated the whole universal algorithm, which works no matter what kind of the matrix we start with.

Keywords:eigenvalues, eigenvectors, minimal polynomial, minimal polynomial of a vector with respect to matrix, generalized eigenvector, Jordan chain of generalized eigenvectors

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