The Wavelet Transform

This volume presents high-level content on the fascinating field of wavelet transform and its applications in real-world phenomena. The book is designed for students, postdocs, and researchers interested in studying the wavelet method and its applications.

This book delves into an exposition on spectral analysis, restoring, monitoring, and signal processing, as well as essential applications required in waveguides and for the improvement of medical images, proving the wavelet transform to be helpful in resolution analysis in time-frequency, with an emphasis on different methods of the calculus using FFT and DSTFT.

This book explores the use of wavelet transforms in signal processing, including image, finance, and communication systems. It covers five contemporary applications, including the interaction between inertial sensors and wavelet filtering techniques, geophysical prospecting, volatility patterns in asset returns, computerized tomography (CT), and fault detection techniques.

This book first details a proposed Stationary Bionic Wavelet Transform (SBWT) for use in speech processing. The author then details the proposed techniques based on SBWT. These techniques are relevant to speech enhancement, speech recognition, and ECG de-noising. The techniques are then evaluated by comparing them to a number of methods existing in literature. For evaluating the proposed techniques, results are applied to different speech and ECG signals and their performances are justified from the results obtained from using objective criterion such as SNR, SSNR, PSNR, PESQ , MAE, MSE and more.

This book looks at some of the most creative and popular applications of wavelets including biomedical signal processing, image processing, communication signal processing, Internet of Things (IoT), acoustical signal processing, financial market data analysis, energy and power management, and COVID-19 pandemic measurements and calculations.