Science Journal of Circuits, Systems and Signal Processing

Special Issue

Signal Processing: Wavelet Analysis and Parameter Estimation

  • Submission Deadline: Oct. 30, 2015
  • Status: Submission Closed
  • Lead Guest Editor: Olusegun Aboaba
About This Special Issue
Signal processing involves the identification, manipulation, modelling and utilisation of the patterns in a signal process. It is generally applied in any system that is concerned with the processing or communication of information. Typical applications of signal processing methods include cellular mobile phones, digital radio and TV, speech recognition, geophysical exploration, and biomedical engineering.

In recent years, the use of wavelet analysis as a signal processing technique has received much attention. Wavelet analysis is a method of converting a signal into some other form, by the use of small wave-like functions known as wavelets, which then enables certain features of the original signal to be more amenable to study. Wavelets can be used to analyse non-stationary or transient signals. For example, wavelets have been used in biomedical engineering for diagnosing cardiovascular disorders, and neurophysiological disorders such as epileptic seizure detection and Alzheimer disease.

The increasing availability of powerful digital computers, in recent years, has been accompanied by advanced digital signal processing algorithms for use in diverse applications; such as in parameter estimation, signal classification, and channel equalisation. This special issue invites original papers in all research and application areas related to signal processing, such as wavelet analysis and parameter estimation.

The topics in this special issue include (but are not limited to):

1. Signal parameter estimation methods
2. Detection of signals in noise
3. Extraction of multipath channel parameters from field measurements
4. Design of optimum FIR linear-phase digital filters
5. Noise reduction techniques
6. Digital signal processing applications
7. Multiresolution signal decomposition
8. Singularity detection with wavelets
9. Multiscale products technique for signal denoising
Lead Guest Editor
  • Olusegun Aboaba

    Department of Electrical and Computer Engineering, Curtin University, Perth, Australia

Guest Editors
  • Ming-Hung Hsu

    Department of Electrical Engineering, National Penghu University of Science and Technology, Penghu, Taiwan

  • Yu Zhang

    School of Engineering, University of Vermont, Burlington, United States

  • Sepehr Nesaei

    Research/Teaching Assistant at Washington State University, Pullman, United States

  • -- --

    --, Australia

  • Laith Abdul-Rahaim

    Electrical Engineering dpartment, Babylon University, United Kingdom

  • anand raj

    Associate Professor, Department of Computer Science and Engineering, SREC, Warangal, Warangal, India

  • Abhishek Tiwari

    Department of Information Technology, ABES Engineering College, Ghaziabad, India

  • Naveen Kolla

    Elecetonics & Communication Engineering, Geethanjali Institute of Science & Technology,Nellore/ Jawharlal Nehru Technological University Ananthapur, Nellore, India

  • shilpa mehta

    ECE , K R Mangalam University, Gurgaon, India

  • Morteza Eliasi

    , Iran

  • esraa mohammed

    , Iraq