A CF-Based Randomness Measure for Sequences
Anvesh Aileni
TL;DR
This paper introduces a new randomness measure for sequences based on the continued fraction representation, quantifying their unpredictability by counting CF components, applicable to PN sequences and other representations.
Contribution
It proposes a novel randomness measure derived from continued fraction components, offering a new way to quantify sequence randomness.
Findings
The measure correlates with sequence unpredictability.
It effectively quantifies randomness in PN sequences.
Comparison shows advantages over fractional representation.
Abstract
This note examines the question of randomness in a sequence based on the continued fraction (CF) representation of its corresponding representation as a number, or as D sequence. We propose a randomness measure that is directly equal to the number of components of the CF representation. This provides a means of quantifying the randomness of the popular PN sequences as well. A comparison is made of representation as a fraction and as a continued fraction.
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Taxonomy
TopicsComputability, Logic, AI Algorithms · Chaos-based Image/Signal Encryption · Numerical Methods and Algorithms