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Lossless compression catalyst based on binary allocation via modular arithmetic.

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TLDR
A new binary (bit-level) lossless compression catalyst method based on a modular arithmetic, called Binary Allocation via Modular Arithmetic (BAMA), has been introduced and allows a significant increase in the compression performance of binary sequences, among others.
Abstract
A new binary (bit-level) lossless compression catalyst method based on a modular arithmetic, called Binary Allocation via Modular Arithmetic (BAMA), has been introduced in this paper. In other words, BAMA is for storage and transmission of binary sequences, digital signal, images and video, also streaming and all kinds of digital transmission. As we said, our method does not compress, but facilitates the action of the real compressor, in our case, any lossless compression algorithm (Run Length Encoding, Lempel-Ziv-Welch, Huffman, Arithmetic, etc), that is, it acts as a compression catalyst. Finally, this catalyst allows a significant increase in the compression performance of binary sequences, among others.

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A universal algorithm for sequential data compression

TL;DR: The compression ratio achieved by the proposed universal code uniformly approaches the lower bounds on the compression ratios attainable by block-to-variable codes and variable- to-block codes designed to match a completely specified source.
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TL;DR: A minimum-redundancy code is one constructed in such a way that the average number of coding digits per message is minimized.
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A method for the construction of minimum-redundancy codes

TL;DR: A minimum-redundancy code is one constructed in such a way that the average number of coding digits per message is minimized.
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The Theory of the Riemann Zeta-Function

TL;DR: The Riemann zeta-function embodies both additive and multiplicative structures in a single function, making it one of the most important tools in the study of prime numbers as mentioned in this paper.