Lectures related to Projections, Transformations: MN03-MN95

Explores geodesy, coordinate transformations, and system design for various locations.

Explores Galilean transformations in spacetime, focusing on measurements and coordinate transformations.

Explores isometries in Euclidean spaces, including translations, rotations, and linear symmetries, with a focus on matrices.

Covers the definition and use of coordinate systems and applications in bases and linear equations.

Explores geodetic references, coordinate systems, GPS applications, and satellite tracking.

Covers 2D transformations, linear maps, matrices, affine transformations, and orthogonal transformations.

Covers Gaussian random variables, affine transformations, and linear systems driven by Gaussian noise in multivariable control.

Covers linear applications, matrices, transformations, and the principle of superposition.

Explores coordinate systems, including polar and curvilinear coordinates, and their transformations.

Explains axonometry, focusing on image of points and true magnitude of segments in 3D space.

Explores the properties and applications of the Fourier transform in signal processing and mathematics.

Illustrates changing basis in linear algebra through a specific example involving a linear transformation in R4.

Explores isometries, distinguishing between rotations and reflections, and the preservation of orientation in geometric transformations.

Explores affine coordinate transformation, satellite tracking, and challenges in map projections.

Covers the concept of affine transformations in functions, including shifting and compressing functions.

Explores Gaussian processes, linear systems, transformations, and noise properties in multivariable control applications.

Explores additional transformations between geocentric and geodetic systems, map projections, and vertical reference systems.

Covers matrix transposition, rank, and basis change in linear algebra, exploring invertibility criteria and basis relationships.

Covers transforming surface normals, forced perspective, shading algorithms, and input values computation in fragment shaders.

Emphasizes the importance of using orthogonal bases in linear algebra for representing linear transformations.