The following links have been developed by BYU graduate students enrolled in ECEn 671 Mathematics of Signals and Systems during Fall Semester 2018.
Topic 2. Vector norms: 1-norm, 2-norm, p-norm, infinity-norm
Topic 3. Inner product and inner product spaces
Topic 5. Orthonormal bases for vector spaces
Topic 7. Gram-Schmidt orthogonalization
Topic 8. Linear regression (least squares)
Topic 9. Dual approximation (min-norm solutions)
Topic 10. Generalized Fourier series
Topic 14. Matrix Inverses and pseudo-inverses
Topic 15. The matrix inversion lemma
Topic 16. Recursive least squares
Topic 18. Cholesky Factorization
Topic 20. Eigenvalues and eigenvectors
Topic 21. The matrix exponential
Topic 22. Differential equations and invariant subspaces
Topic 24. Singular Value Decomposition
Topic 25. The four fundamental spaces of a matrix
Topic 26. Rank reducing approximations of a matrix
Topic 28. Lagrange Multipliers
Topic 29. Kuhn-Tucker Conditions
Appendix. Mathematical Preliminaries
Spline Basis Construction - Julia
Multisource Statistically-Optimized Nearfield Acoustical Holography
https://github.com/randybeard/ece671-jupyter.git
Viewer only: http://nbviewer.jupyter.org/github/randybeard/ece671-jupyter/blob/master/table_of_contents.ipynb
This Jupyter book is mimicking the style of the following book:
http://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python
from book_format import load_style load_style()