Explore >> Select a destination
|
You are here 
|
cyclostationary.blog | ||
| | | | |
distill.pub
|
|
| | | | | How to turn a collection of small building blocks into a versatile tool for solving regression problems. | |
| | | | |
francisbach.com
|
|
| | | | | ||
| | | | |
terrytao.wordpress.com
|
|
| | | | | In preparation for my upcoming course on random matrices, I am briefly reviewing some relevant foundational aspects of probability theory, as well as setting up basic probabilistic notation that we... | |
| | | | |
nhigham.com
|
|
| | | The Cayley-Hamilton Theorem says that a square matrix $LATEX A$ satisfies its characteristic equation, that is $latex p(A) = 0$ where $latex p(t) = \det(tI-A)$ is the characteristic polynomial. This statement is not simply the substitution ``$latex p(A) = \det(A - A) = 0$'', which is not valid since $latex t$ must remain a scalar... | ||
