In this post, we attempt to unravel the mysteries of the “magic” constant found in the fast inverse sqrt method in an intuitive fashion.
In this post, we prove the closed form of a nonlinear recurrence corresponding to the count of binary trees with nodes.
This is inspired by an article of similar name called Calculating Fibonacci Numbers, Quickly and Exactly. Consider the a modified fibonacci sequence given by the recurrence . We shall look at various algebraic and analytic properties of this sequence, find two algorithms that computes in time, and finally look at a motivating example where we need to compute this sequence quickly and exactly.
Suppose that we are given the alphabet ; a word of length : , is an ordered -tuple whose elements all came from . For example, a word of length in might be the tuple , which we will hereon denote as . For some natural number , how many words of length are there that contains exactly zeros?
Suppose that we’re given the function , find the ordinary generating function associated with it in the form of . Furthermore, find/compute .
We consider the problem of efficiently computing the infinity norm of the inverse of a lower bidiagonal matrix L in linear time.
Very short proof that limit preserving functions (continuous functions) on complete partial orders are necessarily monotone.
The first part on a series designed to survey the design and analysis of various numerical methods will look at error propagation.
Let’s take a look at an example of a situation where ambiguity occurs during the derivation of subtyping proofs in Java. In general, it’s conjectured that subtyping in Java is undecidable.
We use a very natural semantic translation from OCaml styled types (or really any almost algebraic types) to the count of the instances of those types and do some cool stuff with this translation.