The stationary bionic wavelet transform and its applications for ECG and speech processing / Talbi Mourad.
Mourad, Talbi, author.
2022
TK7882.S65
Available Online

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Title
The stationary bionic wavelet transform and its applications for ECG and speech processing / Talbi Mourad.
Author
Mourad, Talbi, author.
ISBN
9783030934057 (electronic bk.)
3030934055 (electronic bk.)
9783030934040 (print)
3030934047
DOI
https://doi.org/10.1007/978-3-030-93405-7
Published
Cham, Switzerland : Springer, 2022.
Language
English
Description
1 online resource (xiv, 84 pages) : illustrations (some color).
Item Number
10.1007/978-3-030-93405-7 doi
Call Number
TK7882.S65
Dewey Decimal Classification
621.382/2
Summary
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. Describes and applies a proposed Stationary Bionic Wavelet Transform (SBWT) Discusses how speech enhancement, speech recognition, and ECG de-noising are aided by SBWTs Relevant to researchers, professionals, students, and academics in speech and ECG processing.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed February 17, 2022).
Series
Signals and communication technology, 1860-4870
Available in Other Form
Print version: 9783030934040
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
1. Speech enhancement based on stationary bionic wavelet transform and maximum a posterior estimator of magnitude-squared spectrum
2. ECG denoising based on 1-D double-density complex DWT and SBWT
3. Speech Enhancement based on SBWT and MMSE Estimate of Spectral Amplitude
4. Arabic Speech Recognition by Stationary Bionic Wavelet Transform and MFCC using a Multi-Layer Perceptron for Voice Control.

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