The question of similarity of matrices cannot be solved in general using only the tools of a first course in linear algebra. But if you are interested only in having an effective procedure, the …

Jan 8, 2014 · I'm taking the course Linear Algebra 1, and recently we've learned about matrix similarity. What is the motivation defining it? or, What are the uses/applications for this definition?

There are many ways to measure the "distance" between two matrices (just as there are many ways to measure the distance between two vectors). Without some more information, it's …

Mar 2, 2016 · Are there any measures of similarity or distance between two symmetric covariance matrices (both having the same dimensions)? I am thinking here of analogues to KL …

Jan 3, 2014 · Assuming the eigenvalues of a matrix are distinct it is diagonalizable. If two matrices are both diagonalizable with the same distinct eigenvalues then they are similar. (To see this …

May 18, 2017 · Do you just have think up a matrix P P or is there a systematic way of finding it? A second question I have if I have a matrix A A and find its eigenvectors, and place these in my …

Jun 1, 2016 · Some Google search led me to matrix similarity, and my algebraic intuition says that this information would be codified in the quotient structure - once we ''kill' the big structure by …

Scalar product is also called an angle-type similarity between 1 and 2, and in Euclidean space it is geometrically the most valid similarity measure, because it is easily converted to the euclidean …

Ok! But If I understand right you don't really convert the euclidean distance into a similarity, but you just use a different function that returns you values within 0 and 1 (because of the cosine), …

May 5, 2015 · I want to create heatmaps based upon cosine dissimilarity. I'm using R and have explored several packages, but cannot find a function to generate a standard cosine …