Abstract. In this paper we consider a discrete version of the Bernoulli convolution problem traditionally studied via functional analysis. We discuss several innovative algorithms for computing the sequences with this new approach. In particular, these algorithms assist us in gathering data regarding the maximum values. By looking at a family of associated polynomials, we gain insight on the local behavior of the sequence itself. This work was completed as part of the Clemson University REU, an NSF funded program 1 .

Abstract. In this paper we consider a discrete version of the Bernoulli convolution problem traditionally studied via functional analysis. We develop an algorithm which bounds the Bernoulli sequences, and we give a significant improvement on the best known bound.