Sequence Randomization Using Convolutional Codes and Probability Functions

TL;DR

This paper explores a method combining convolutional codes and probability functions to enhance sequence randomness, effectively transforming correlated sequences into more random ones.

Contribution

It introduces a novel approach that integrates convolutional codes with probability functions for improved sequence randomization.

Findings

Convolutional codes increase sequence size and randomness.

The method effectively converts correlated sequences into random sequences.

The approach enhances sequence randomness for various applications.

Abstract

This paper investigates the use of different transformations for improving the randomness of sequences. In particular, convolutional codes are used for increasing the size of a given sequence and then a random mapping function is used for further randomization. We have shown how such a method can convert highly correlated sequences into random ones.