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Fractal-Wavelet Techniques in Signal Processing Theory and Applications

Nowadays, the world of the telecommunications uses frequently wavelet analysis and fractal geometry to improve techniques and models in signal theory. Several publications have appeared in recent years due to their applications to pure and applied science. In particular, fractal sets are nowadays applied in image processing, image compression, etc. Likewise, wavelet analysis has become popular and important in telecommunications due mainly to several applications in signal processing, information theory, remote sensing, etc. In particular, signal processing has shown that the fractal-wavelet approach can shed some new light on several unsolved problems. In fact, nonlinear models are often described and approximated by pre-fractal sets and wavelet expansions, respectively. As a result, a fractal-wavelet approach is capable of providing ever more refined models for applications in signal processing. The choice of pre-fractal set and wavelet basis relies on technical requirements and nature of the problem. 

Guest Editors
Emanuel Guariglia, Wenzhou-Kean University, China
Rodrigo C. Guido, São Paulo State University, Brazil

Collection articles

  1. Suppressing random noise in seismic signals is an important issue in research on processing seismic data. Such data are difficult to interpret because seismic signals usually contain a large amount of random n...

    Authors: Feng Yang, Jun Liu, Qingming Hou and Lu Wu
    Citation: EURASIP Journal on Advances in Signal Processing 2024 2024:65
  2. In view of the serious color and definition distortion in the process of the traditional image fusion, this study proposes a Haar-like multi-scale analysis model, in which Haar wavelet has been modified and us...

    Authors: Xiaoliang Zhu and Mengke Wen
    Citation: EURASIP Journal on Advances in Signal Processing 2024 2024:23
  3. This paper proposes a classification method for financial time series that addresses the significant issue of noise. The proposed method combines improved complete ensemble empirical mode decomposition with ad...

    Authors: Bing Liu and Huanhuan Cheng
    Citation: EURASIP Journal on Advances in Signal Processing 2024 2024:19
  4. The surface electromyography (sEMG) signal presents significant challenges for the dynamic analysis and subsequent examination of muscle movements due to its low signal energy, broad frequency distribution, an...

    Authors: Chuanyun Ouyang, Liming Cai, Bin Liu and Tianxiang Zhang
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:108
  5. The analysis of underwater discharge signals is of great significance for its application. Wavelet-based de-noising and analysis technology is an effective means to study underwater discharge signals. The sele...

    Authors: Xiaobing Zhang, Binjie Lu and Liang Qiao
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:106