Half-infinite sampling and its FT

TL;DR

This paper introduces the concept of half-infinite sampling, deriving its Fourier transform to provide a more concise representation of finite signals, supported by theoretical analysis and numerical experiments.

Contribution

It proposes half-infinite sampling as a new perspective, deriving its Fourier transform to improve understanding and representation of finite signals in signal processing.

Findings

FT of half-infinite sampling is more concise than that of infinite sampling

Numerical experiments verify the theoretical derivations

Step sampling and interesting equations are introduced

Abstract

In the digital world, signals are discrete and finite. The Fourier representation of discrete and finite signals is FT convolution of the finite sampling function and the continuous signal. Conventionally, finite sampling is treated as a segment of infinite sampling. Though this approach perfectly solves the difference between finite and infinite sampling, it has caused much trouble for signal processing. Mathematically, there is a kind of sampling between finite and infinite sampling, and we name this kind of sampling as half-infinite sampling. Theoretically, finite sampling can also be treated as a segment of half-infinite sampling. Because we can derive the Fourier representation of discrete and finite signals from half-infinite sampling, the FTs of several half-infinite samplings are studied. The results show that the FT of half-infinite sampling is more concise than that of infinite sampling. A numerical experiment verified the theoretical derivations successfully, during which step sampling was proposed. Besides, several interesting equations were built.