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Frequency and Time—Frequency Domain Analysis Tools in Measurement

Pedro M. Ramos, Raul Carneiro Martins, Sergio Rapuano, Pasquale Daponte

Open publisher page 4 citations

Abstract

A traditional approach to signal processing has been, for a long time, the frequency domain analysis, in which time or space periodicities can be identified. It is a relatively simple approach which usually carries significant information, suitable both as a first-step approach for further signal processing and for feature extraction. Because this approach carries no time information, frequency and time-domain analysis based on wavelets has become increasingly important. This shares a similar analytical approach making use of time-limited functions as the basis of the transform, allowing for space or time localization of short-lived repeating patterns. These are signal-processing tools which require some good understanding of the underlying theory to avoid common pitfalls and circumvent some limitations. Examples are given to show applicability.

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What this paper is about

A traditional approach to signal processing has been, for a long time, the frequency domain analysis, in which time or space periodicities can be identified. It is a relatively simple approach which usually carries significant information, suitable both as a first-step approach for further signal processing and for feature extraction. Because this approach carries no time information, frequency and time-domain analysis based on wavelets has become increasingly important. This shares a similar analytical approach making use of time-limited functions as the basis of the transform, allowing for space or time localization of short-lived repeating patterns. These are signal-processing tools which require some good understanding of the underlying theory to avoid common pitfalls and circumvent some limitations. Examples are given to show applicability.

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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

A traditional approach to signal processing has been, for a long time, the frequency domain analysis, in which time or space periodicities can be identified. It is a relatively simple approach which usually carries significant information, suitable both as a first-step approach for further signal processing and for feature extraction. Because this approach carries no time information, frequency and time-domain analysis based on wavelets has become increasingly important. This shares a similar analytical approach making use of time-limited functions as the basis of the transform, allowing for space or time localization of short-lived repeating patterns. These are signal-processing tools which require some good understanding of the underlying theory to avoid common pitfalls and circumvent some limitations. Examples are given to show applicability.

Key concepts: Frequency domain, Time–frequency analysis, Computer science, Signal processing, Time domain, SIGNAL (programming language), Wavelet, Simple (philosophy)

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