T. S. Blyth's research while affiliated with University of St Andrews and other places

Publications (26)

Book
Preface.- Foreward.- The Algebra of Matrices.- Some Applications of Matrices.- Systems of Linear Equations.- Invertible Matrices.- Vector Spaces.- Linear Mappings.- The Matrix Connection.- Determinants.- Eigenvalues and Eigenvectors.- The Minimal Polynomial.- Solutions to the Exercises.- Index.
Chapter
By a relation between sets A and B we shall mean intuitively a sentence S (x, y) from which, on substituting for x an object of A and for y an object of B, we obtain a meaningful sentence that can be classified as true or false.
Book
Incluye índice v. 1. Sets and mappings -- v. 2. Matrices and vector spaces -- v. 3. Abstract algebra -- v. 4. Linear algebra -- v. 5. Groups.
Chapter
Our approach to the theory of sets will be naïve in the sense that, rather than give a precise definition of the concept of a ‘set’, we shall rely heavily on intuition. By a set we shall mean a ‘collection of objects’, these objects being anything we care to imagine. The objects that make up a given set E are called the elements of E. We express th...
Chapter
The most important type of mapping is certainly a bijection. In this Chapter we shall be particularly interested in the set of bijections on a given finite set.
Chapter
We now turn our attention to a specific set, namely the set ℤ of integers. The subset IN of natural numbers will play an important part in the discussion. We begin by considering the notion of an ordered set.
Chapter
It can be justifiably argued that during the last century the theory of sets has revolutionized the whole of mathematics. One of the major achievements that has resulted from the development of set theory is a clear interpretation of the concept of ‘infinity’. Our objective in this final Chapter is to make this concept precise, and in so doing give...
Chapter
Our objective now is to obtain an answer to the question: under what conditions is an n × n matrix A similar to a diagonal matrix? In so doing, we shall draw together all the notions that have been developed previously. Unless otherwise specified, A will denote an n × n matrix over IR or ℂ.
Chapter
In what follows it will prove convenient to write an n × n matrix A in the form $$A = \left[ {a_1 ,a_2 \ldots ,a_n } \right]$$ where, as before, the notation ai represents the i-th column of A. Also, the letter F will signify as usual either the field IR of real numbers or the field ℂ of complex numbers.
Chapter
We now consider the simple, but very important, notion of a collection of pairwise disjoint subsets that fit together like a jig-saw puzzle.

Citations

... In particular, we prove that Lip(µ, 1) is the dual space of the generalization B(µ, 1) of the special atom space to general measures µ on [0, 2π]. We start with the definition of the Lipschitz condition for some functions, which the reader can find in any undergraduate or graduate text in Analysis, including [7]. Definition 1.1. ...
... Çalışmada kullanılacak temel bilgiler tanım, önerme, teorem ve açıklamalar biçiminde bu bölümde takdim edilecektir. Referansları açık olarak verilmeyen cebirsel bilgiler için [14][15][16][17][18][19] daki çalışmalardan faydalanılmıştır. ...
... We construct the inertia tensor of the given object [20] which is a 3x3 matrix (if we want only geometrical measure, we will use a mass of 1 for all points and if we want a measure with physical and chemical meaning we can use the actual masses of the atoms). Eigen-decomposition techniques [21,22] are used to find the eigenvalues and eigenvectors of the inertia matrix (as this is a symmetric, real, positive definite, 3x3 matrix it can be decomposed easily using various techniques. We used the explicit analytical solution for the characteristic polynomial [22] ). ...
... • When the linear subspaces X and Y are orthogonal, it holds that X + Y = X ⊕ Y, where ⊕ stands for the orthogonal direct sum 14 [49]. In order to emphasize the orthogonal relations of subspaces, when X ⊥ Y we will often write X ⊕ Y instead of X + Y. ...
... Matrices acts as foundation in Mathematics, Science, Economics and many other fields. Not only in theoretical aspect but matrices have real life applications [7], [8], [9], [10]. ...
... Los libros principales en que está basado el capítulo son [12,18,24]. Para ampliar los temas mencionados puede encontrar en los textos [6,15,21]. Si (x 2 − x − 11, 10) = (1, y 2 − 3y), encontrar x − y. ...
... where D is a two-dimensional matrix of intensities as a function of reaction time and frequency, K is two-dimensional array of the time-dependent concentration profiles of each component and S T is the transpose of the spectra of the pure components [4]. The MCR-ALS algorithm uses Eq. (3) to determine the concentration profiles and pure component spectra by solving for K and S T in an iterative fashion until a minimal error is obtained [2,5]. ...