Sequence Randomization Using Convolutional Codes and Probability Functions
This addresses the problem of sequence randomness for applications requiring uncorrelated data, but it appears incremental as it builds on existing methods like convolutional codes.
The paper tackled the problem of improving sequence randomness by using convolutional codes to increase sequence size and a random mapping function for further randomization, resulting in the conversion of highly correlated sequences into random ones.
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.