Homogeneity: T(c * u) = c * T(u) for any scalar c and vector u. Additivity: T(u + v) = T(u) + T(v) for any vectors u and v. The range of a linear transformation T is the set of all vectors that can be ...

This course focuses on lines and planes, the geometry and algebra of vectors, systems of linear equations, matrix algebra, linear independence, spanning sets, basis, linear transformations, ...

Abstract: This book contains a detailed discussion of the matrix operation, its properties, and its applications in finding the solution of linear equations and determinants. Linear algebra is a ...

Topics include systems of linear equations, matrix algebra, elementary matrices, and computational issues. Other areas of the course focus on the real n-space, vector spaces and subspaces, basis and ...

MATH 146 is an advanced-level version of MATH 136. Topics includes vector spaces, linear dependence and span, bases and dimension, linear transformations, rank, change of coordinate matrices, and ...

If \(A\) is a \(3\times 3\) matrix then we can apply a linear transformation to each rgb vector via matrix multiplication, where \([r,g,b]\) are the original values ...

Self-funded student: register by the 10th of the month, start on the 1st of the next. Funded student: please check the next enrolment deadline and course start date. Mathematics Diagnostic Assessment.

Vector spaces, linear transformation, matrix representation, inner product spaces, isometries, least squares, generalised inverse, eigen theory, quadratic forms, norms, numerical methods. The fourth ...