Engineering Analysis/Vector Spaces
|Before reading this chapter, students should know the terms vector, scalar, and matrix. These terms are discussed in Linear Algebra.|
Vectors and Scalars[edit | edit source]
A scalar is a single number value, such as 3, 5, or 10. A vector is an ordered set of scalars.
A vector is typically described as a matrix with a row or column size of 1. A vector with a column size of 1 is a row vector, and a vector with a row size of 1 is a column vector.
A "common vector" is another name for a column vector, and this book will simply use the word "vector" to refer to a common vector.
Vector Spaces[edit | edit source]
A vector space is a set of vectors and two operations (addition and multiplication, typically) that follow a number of specific rules. We will typically denote vector spaces with a capital-italic letter: V, for instance. A space V is a vector space if all the following requirements are met. We will be using x and y as being arbitrary vectors in V. We will also use c and d as arbitrary scalar values. There are 10 requirements in all:
- There is an operation called "Addition" (signified with a "+" sign) between two vectors, x + y, such that if both the operands are in V, then the result is also in V.
- The addition operation is commutative for all elements in V.
- The addition operation is associative for all elements in V.
- There is a unique neutral element, φ, in V, such that x + φ = x. This is also called a zero element.
- For every x in V, then there is a negative element -x in V such that -x + x = φ.
- 1 × x = x
Some of these rules may seem obvious, but that's only because they have been generally accepted, and have been taught to people since they were children.