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Intelligent Digital Signal Processing and Feature Extraction Methods

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New Approaches in Intelligent Image Analysis

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 108))

Abstract

Intelligent systems comprise a large variety of applications, including ones based on signal processing. This field benefits from considerable popularity, especially with recent advances in artificial intelligence, improving existing processing methods and providing robust and scalable solutions to existing and new problems. This chapter builds on well-known signal processing techniques, such as the short-time Fourier and wavelet transform, and introduces the concept of instantaneous frequency along with implementation details. Applications featuring the presented methods are discussed in an attempt to show how intelligent systems and signal processing can work together. Examples that highlight the cooperation between signal analysis and fuzzy c-means clustering, neural networks and support vector machines are being presented.

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Author information

Authors and Affiliations

  1. Technical University of Cluj Napoca, 128-130 21 December 1989 Boulevard, 400604, Cluj Napoca, Romania

    János Szalai

  2. Petru Maior University of Târgu Mures, 1 Nicolae Iorga Street, 540088, Târgu Mures, Romania

    Ferenc Emil Mózes

Authors
  1. János Szalai
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  2. Ferenc Emil Mózes
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Correspondence to János Szalai .

Editor information

Editors and Affiliations

  1. Technical University of Sofia, Sofia, Bulgaria

    Roumen Kountchev

  2. University of Hyogo, Chuo-ku, Japan

    Kazumi Nakamatsu

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Szalai, J., Mózes, F.E. (2016). Intelligent Digital Signal Processing and Feature Extraction Methods. In: Kountchev, R., Nakamatsu, K. (eds) New Approaches in Intelligent Image Analysis. Intelligent Systems Reference Library, vol 108. Springer, Cham. https://doi.org/10.1007/978-3-319-32192-9_2

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  • DOI: https://doi.org/10.1007/978-3-319-32192-9_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32190-5

  • Online ISBN: 978-3-319-32192-9

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