Signal Approximation and Orthogonal Bases

Related lectures (31)

Page 3 of 4

Introduces mechanics, differential and vector calculus, and historical perspectives from Aristotle to Newton.

Covers orthogonal linear maps, orthogonal matrices, invertibility, and least squares solutions in Euclidean spaces.

Covers the fundamental concepts of vectors, including their characteristics and calculation methods.

Introduces orthogonal vectors, scalar product, Euclidean norm, Pythagorean theorem, and unit vectors.

Introduces the first step in finding an orthogonal/orthonormal base in a vector space.

Introduces orthogonal and orthonormal families in vector spaces with scalar products.

Covers vector spaces, scalar products, norms, and forms of polarization in standard properties.

Explores rectilinear movement, vector algebra, scalar products, and vector decomposition in a three-dimensional space.

Explores multilinear regression, variance, correlation, optimization, ANOVA, and design procedures.

Covers Fourier analysis, series convergence, divergence theorem, and vector analysis.