matrices

Imagine you are forced to never change an array of numbers for an algorithm computing matrices, rather creating new matrices for each step and specifying numbers only during initialization.

Especially complicated expressions within matrices (or things like that which quickly turn into a jumbled mess in TeX).

Its redeeming feature is its native support for matrices, including its ability to transparently parallelise operations on them.

He gives a brief overview of classical complexity, how quantum matrices work, then how quantum complexity works.

However, this isn't what caused me to abandon the library, it was the lack of support for 3-dimensional matrices.

This is a great textbook that shows you how matrices are defined from fields, etc… (i.e.

Rather, the order in which the elements in the matrices are being multiplied is changed.

He showed me some work he was doing related to what happens to the determinants of matrices when you sum then.

It’s a useful desktop calculator that hangles big int, rational and floating-point numbers, vectors, matrices.

Why on earth would you use game theory's payoff matrices as an analogy to what could perfectly be put into words?

Whether you are solving matrices or simulating aerodynamics, the cost of doing certain tasks and prototyping has reduced to almost zero thanks to computers.

It has very good support for sparse matrices (package Matrix) and also for serializing big data structures and loading parts in memory sequentially (like SAS).

Likely, it doesn't accept complex numbers (or vectors or matrices) as input as part of the (implicit) spec: in common parlance, "number" tends to mean real number.

If you interpret "array programming language" as "language with support for arrays and matrices as first-class objects with nice operators, etc" then you get a lot more things coming into the mix beyond oddballs like apl.

But for many, having a well-practiced ability to do operations on matrices and vectors first (even if it's just a bunch of magic formuas) allows them to learn the more basic facts via experimentation, because they don't get "stuck" right at the beginning.