The dimension of the tensor is called its rank.īut this description misses the most important property of a tensor!Ī tensor is a mathematical entity that lives in a structure and interacts with other mathematical entities. That is, it could be a 1-D matrix (a vector is actually such a tensor), a 3-D matrix (something like a cube of numbers), even a 0-D matrix (a single number), or a higher dimensional structure that is harder to visualize. ![]() ![]() The basic idea, though, is that a matrix is just a 2-D grid of numbers.Ī tensor is often thought of as a generalized matrix. So there are a bunch of mathematical operations that we can do to any matrix. A vector is a matrix with just one row or column (but see below). We can add and subtract matrices of the same size, multiply one matrix with another as long as the sizes are compatible (( n × m) × ( m × p) = n × p), and multiply an entire matrix by a constant. ![]() Then we can take a look at an application to get a little more insight.Ī matrix is a grid of n × m (say, 3 × 3) numbers surrounded by brackets. There is a short answer to this question, so let’s start there.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |