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Abstrak :
This book is a guide to understanding and using the software package ARPACK to solve large algebraic eigenvalue problems. The software described is based on the implicitly restarted Arnoldi method, which has been heralded as one of the three most important advances in large scale eigenanalysis in the past ten years. The book explains the acquisition, installation, capabilities, and detailed use of the software for computing a desired subset of the eigenvalues and eigenvectors of large (sparse) standard or generalized eigenproblems. It also discusses the underlying theory and algorithmic background at a level that is accessible to the general practitioner.

Abstrak :
Large-scale problems of engineering and scientific computing often require solutions of eigenvalue and related problems. This book gives a unified overview of theory, algorithms, and practical software for eigenvalue problems. It organizes this large body of material to make it accessible for the first time to the many nonexpert users who need to choose the best state-of-the-art algorithms and software for their problems. Using an informal decision tree, just enough theory is introduced to identify the relevant mathematical structure that determines the best algorithm for each problem. The algorithms and software at the "leaves" of the decision tree range from the classical QR algorithm, which is most suitable for small dense matrices, to iterative algorithms for very large generalized eigenvalue problems. Algorithms are presented in a unified style as templates, with different levels of detail suitable for readers ranging from beginning students to experts. The authors' comprehensive treatment includes a treasure of further bibliographic information.

Abstrak :
Graf Cayley dari grup Γ dengan himpunan penghubung S ⊆ Γ, dinyatakan sebagai Cay(Γ, S), adalah graf dengan himpunan simpul elemen-elemen Γ dan himpunan busur yang berisi busur xy yang memenuhi x · y −1 ∈ S untuk setiap x, y ∈ S. Matriks antiketetanggaan adalah salah satu cara representasi graf. Pada penelitian ini, diselidiki nilai eigen matriks antiketetanggaan graf Cay(Zn, S), dengan S ⊆ Zn − {0}. Untuk meneliti sifat nilai eigen matriks antiketetanggaan Cay(Zn, S), digunakan sifat nilai eigen matriks sirkulan. Dari bentuk umum nilai eigen matriks sirkulan, diturunkan sifat-sifat nilai eigen matriks antiketetangggaan Cay(Zn, S), dengan berbagai variasi himpunan S. Selain itu, diselidiki relasi nilai eigen matriks antiketetanggaan Cay(Zn, S) dengan matriks representasi graf Cayley Zn lainnya ......Cayley graph of group Γ with a connection set S ⊆ Γ, denoted by Cay(Γ, S), is a graph with Γ as vertex set and arcs set consisting of xy for all x, y ∈ Γ such that x · y −1 ∈ S . Antiadjacency matrix is one way of representing a graph. In this research, we investigate the properties of the eigenvalues of antiadjacency matrix of graph Cay(Zn, S). To find the eigenvalues of antiadjacency matrix of Cay(Zn, S), we use the properties of eigenvalues of circulant matrices. From this, the properties of eigenvalues of antiadjacency matrix of Cay(Zn, S), with arbitrary S, is derived. The relation between eigenvalues of antiadjacency matrix of Cay(Zn, S) and other matrix representations of Cayley graph of Zn is also explained.

Abstrak :
Sebuah graf berarah dapat direpresentasikan kedalam beberapa macam bentuk matriks, salah satunya adalah dengan matriks anti-adjacency. Matriks anti-adjacency merupakan sebuah matriks dimana entri-entri dari matriks ini dapat diinterpretasikan sebagai ada atau tidaknya busur berarah dari suatu simpul ke simpul lainnya. Paper ini akan berfokus pada matriks anti-adjacency dari gabungan graf lingkaran berarah. Matriks anti-adjacency adalah sebuah matriks persegi, oleh sebab itu dapat dicari persamaan karakteristik serta nilai eigen dari matriks tersebut. Untuk mencari bentuk umum persamaan karakteristik matriks anti-adjacency dari gabungan graf lingkaran berarah diperoleh dengan cara menghitung nilai determinan dan banyaknya subgraf-subgraf terinduksi pada setiap grafnya. Dengan mencari akar-akar dari bentuk umum persamaan karakteristik matriks anti-adjacency dari gabungan graf lingkaran berarah tersebut, maka akan didapatkan nilai eigen dari graf tersebut. ......A graph could be represented as a matrix in many ways, one of which is an anti-adjacency matrix. Anti-adjacency matrix is a matrix whose entries shows whether there is a directed edge from a vertex to another one. This paper focuses on the anti-adjacency matrix of the union of directed cycle graphs. Anti-adjacency matrix is a square matrix, where we could find its characteristic polynomial and eigenvalues. The general form of characteristic polynomial can be found by counting the values of the determinants and the numbers of the cyclic induced subgraphs. Furthermore, the eigenvalues of the union of directed cycle graphs are derived from the general form of its characteristic polynomial.

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.

Abstrak :
This paper presents a novel analytical methodology to determine location for reactive power devices placement in power systems. The proposed method modifies modal analysis technique and develops new formulation to compute the Reactive Contribution Factor (RCF) of each load buses based on the inversed reduced Jacobian matrix. The objective of this research is to achieve the most stable condition as well as to minimize network losses. The proposed method is implemented at the modified IEEE 30-bus Reliability Test System (RTS) and compared with different placement. This work compares the voltage profile, eigenvalue and network losses to assess the method. The simulation results show the proposed method can provide a solution to the ideal shunt compensator placement to improve the system’s voltage stability and minimizing losses.