Vector Matrix

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Appendix A

Vectors and Matrices

This appendix provides a refresher in vector and matrix algebra to support the main body of the book. Introductions to vectors and matrices are followed by descriptions of special matrix types, matrix inversion, and vector and matrix calculus.

A.1 Introduction to Vectors

A vector is a single-dimensional array of single-valued parameters, known as scalars.Here scalars are represented as italic and vectors as bold lower case. The scalarcomponents of a vector are denoted by the corresponding italic symbol with a single numerical index and are normally represented together as a bracketed column. Thus,

(A.1)

where, in this case, the vector has n components or elements. Vectors may also be represented with an underline, , or an arrow, , while many authors do not limit them to lower case. Sometimes, it is convenient to represent a vector column on one line. Here, the notation is used. A vector is often used to represent a quantity that has both magnitude and direction; these vectors usually have three components. However, the components of a vector may also be unrelated, with different units. Both types of vector are used here.

Vectors are added and subtracted by adding and subtracting the components:

(A.2)

The corresponding components must have the same units. A vector is multiplied by a scalar simply by multiplying each component by that scalar:
(A.3)

where two vectors have the same length, a scalar may be obtained by summing the products of the corresponding components. This is known as the scalar product or dot product and is written as

(A.4)

Each component product, , must have the same units. Scalar products have the properties

(A.5)

where the ...

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... are, respectively, the adjoint and determinant of A. For an m × n matrix, these are given by:

(A.33)

where r is an arbitrary row and is the minor, the determinant of A excluding row r and column i. The solution proceeds iteratively, noting that the determinant of a 2 × 2 matrix is Alternatively, many numerical methods for matrix inversion are available.

A.5 Calculus

The derivative of a vector or matrix with respect to a scalar simply comprises the derivatives of the elements. Thus,

(A.34)

The derivative of a scalar with respect to a vector is written as the transposed vector of the partial derivatives with respect to each vector component. Thus,

(A.35)

Post-multiplying this by the vector b then produces a scalar with the same units as a. The derivative of one vector with respect to another is then a matrix of the form:

(A.36)

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