English

Orthogonal and Non-Orthogonal Signal Representations Using New Transformation Matrices Having NPM Structure

Signal Processing 2021-07-14 v1 Information Theory math.IT

Abstract

In this paper, we introduce two types of real-valued sums known as Complex Conjugate Pair Sums (CCPSs) denoted as CCPS(1)^{(1)} and CCPS(2)^{(2)}, and discuss a few of their properties. Using each type of CCPSs and their circular shifts, we construct two non-orthogonal Nested Periodic Matrices (NPMs). As NPMs are non-singular, this introduces two non-orthogonal transforms known as Complex Conjugate Periodic Transforms (CCPTs) denoted as CCPT(1)^{(1)} and CCPT(2)^{(2)}. We propose another NPM, which uses both types of CCPSs such that its columns are mutually orthogonal, this transform is known as Orthogonal CCPT (OCCPT). After a brief study of a few OCCPT properties like periodicity, circular shift, etc., we present two different interpretations of it. Further, we propose a Decimation-In-Time (DIT) based fast computation algorithm for OCCPT (termed as FOCCPT), whenever the length of the signal is equal to 2v, vN2^v,\ v{\in} \mathbb{N}. The proposed sums and transforms are inspired by Ramanujan sums and Ramanujan Period Transform (RPT). Finally, we show that the period (both divisor and non-divisor) and frequency information of a signal can be estimated using the proposed transforms with a significant reduction in the computational complexity over Discrete Fourier Transform (DFT).

Keywords

Cite

@article{arxiv.2107.06173,
  title  = {Orthogonal and Non-Orthogonal Signal Representations Using New Transformation Matrices Having NPM Structure},
  author = {Shaik Basheeruddin Shah and Vijay Kumar Chakka and Arikatla Satyanarayana Reddy},
  journal= {arXiv preprint arXiv:2107.06173},
  year   = {2021}
}

Comments

13 pages, 5 figures,