Data Compression: Multi-Term Approach

TL;DR

This paper introduces a multi-term transform (MTT) for signal data compression that enhances accuracy by optimizing additional parameters and extending known transform structures, leading to improved performance.

Contribution

It proposes a novel multi-term transform with more parameters and a special transformation to reduce computational load, outperforming existing optimal transforms.

Findings

MTT can provide better accuracy than known optimal transforms under certain conditions.

The extended structure with additional terms improves the transform's performance.

A special transformation reduces numerical load during computation.

Abstract

In terms of signal samples, we propose and justify a new rank reduced multi-term transform, abbreviated as MTT, which, under certain conditions, may provide better-associated accuracy than that of known optimal rank reduced transforms. The basic idea is to construct the transform with more parameters to optimize than those in the known optimal transforms. This is realized by the extension of the known transform structures to the form that includes additional terms - the MTT has four matrices to minimize the cost. The MTT structure has also a special transformation that decreases the numerical load. As a result, the MTT performance is improved by the variation of the MTT components.