The Stationary Bionic Wavelet Transform and its Applications for ECG and Speech Processing: Signals and Communication Technology
Autor Talbi Mouraden Limba Engleză Paperback – 16 feb 2023
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Paperback (1) | 742.63 lei 6-8 săpt. | |
Springer International Publishing – 16 feb 2023 | 742.63 lei 6-8 săpt. | |
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Springer International Publishing – 15 feb 2022 | 748.39 lei 6-8 săpt. |
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Specificații
ISBN-13: 9783030934071
ISBN-10: 3030934071
Pagini: 84
Ilustrații: XIV, 84 p. 69 illus., 50 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.15 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria Signals and Communication Technology
Locul publicării:Cham, Switzerland
ISBN-10: 3030934071
Pagini: 84
Ilustrații: XIV, 84 p. 69 illus., 50 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.15 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria Signals and Communication Technology
Locul publicării:Cham, Switzerland
Cuprins
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
Notă biografică
Mourad Talbi is an Assistant Professor in Electrical Engineering in the Center of Researches and Technologies of Energy of Borj Cedria, Tunis, Tunisia. He has obtained his Master degree in automatics and signal processing in National Engineering School of Tunis in 2004. He has obtained his PhD Thesis in Electronics in Faculty of Sciences of Tunis, and his HDR in Electronics in Faculty of sciences of Tunis.
Textul de pe ultima copertă
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
Caracteristici
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