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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

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    Authors: Chuanyun Ouyang, Liming Cai, Bin Liu and Tianxiang Zhang
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