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Wavelet signals processing

Yu. G. Gorshkov

The monograph describes new promising wavelet-based methods for processing of voice and acoustic biomedical signals, the hardware and software for applied problems of forensic investigation of phonograms, the assessments of human emotional state, noise cleaning and speech scrambling, as well as the construction of biomedical systems for diagnosis of heart and lung diseases.
The study focuses on the development of wavelet technologies for high-precision analysis of voice and acoustic biomedical signals. The solutions of multi-level wavelet transform, which make it possible to visualize non-stationary signals with higher time-frequency resolution, are offered for the first time. The study considers voice protection tools, describes algorithms and software for scrambling voice and acoustic biomedical signals using wavelets. The study introduces a new-generation telemedicine system with scrambling acoustic biomedical signals.
It is intended for scientists and engineers working on the creation of biomedical signal processing means based on new principles. It may be useful to teachers, graduate students and students of technical universities.



М: Publisher «Radiotekhnika», 2017 y. – 240 pages:

ISBN 978-5-93108-138-0
Format: 60x90/16, Binding, cover

1 WAVELET SIGNAL PROCESSING

1.1. Mathematical concepts of the wavelet theory

1.1.1. Signal space and its bases

1.1.2. Scalar product of functions

1.1.3. Norm of the function

1.1.4. Orthogonality and orthonormality

1.1.5. Riesz basis

1.2. Fundamentals of the wavelet transform theory

1.2.1. Idea of the wavelet transform

1.2.2. Approximating and detailing components of the wavelet analysis and signal synthesis  

1.2.3. Continuous direct wavelet transform

1.2.4. Examples of direct wavelet transform

1.2.5. Wavelets in the frequency domain

1.2.6. Backward continuous wavelet transform

1.2.7. Comparison of different representations of signals

1.2.8. Computational speed in wavelet transforms

1.3. Multiple-scale analysis

1.3.1. Concept of orthogonal wavelets

1.3.2. Dyadic wavelet transform of continuous signals

1.3.3. Features of the multiple-scale analysis

1.3.4. Tools of the multiple-scale analysis

1.4. Frequency approach and fast wavelet transform

1.4.1. Frequency approach to wavelet transforms

1.4.2. Fundamentals of wavelet filtration

1.4.3. Quadrature filters

1.4.4. Fast wavelet transform and the Mallat algorithm

1.5. Special issues of wavelet transforms

1.5.1. Wavelet packets

1.5.2. Discrete wavelet analysis and time series

1.6. Construction of wavelets

1.7. Comparison of different types of wavelets

1.7.1. “Crude” wavelets

1.7.2. Continuous regular wavelets

1.7.3. Orthogonal wavelets with compact support

1.7.4. Biorthogonal wavelet pairs with compact support

1.7.5. Complex wavelets

1.8. Limitations and drawbacks of the Fourier transform

1.9. Glossary

2 VOICE SIGNAL ANALYSIS

2.1. Human organs of speech  

2.2. Main characteristics of the voice signal

2.3. Computer speech research  

2.3.1. Spectral decomposition of the voice signal using fast Fourier transform

2.3.2. Speech analysis programs using fast Fourier transform

2.3.3. WaveView wavelet analysis program  

2.3.4. SoundEdit sound editor

2.4. “Fon” research complex for frequency-time analysis  of the voice signal using the wavelet technology  

2.4.1. Structure of “Fon” research complex

2.4.2. WaveView-4 special software

2.4.3. Visualization of time-frequency characteristics of the vowels and consonants of speech

3 PHONOGRAM FORENSIC INVESTIGATION TOOLS

3.1. Hardware-software complexes for forensic investigation of phonograms using Fourier analysis  

3.2. Mixed-level-wavelet-analysis-based hardware-software complexes for forensic investigation of phonograms  

3.2.1. Fon-NI complex  

3.2.2. Expert MWA complex

3.3. Authentication of phonograms

3.4. Assessment of a person’s emotional state based on the voice signal

3.5. Speaker identification based on the construction of  high-precision “phonic portraits” of vowels

3.6. Visualization of the acoustic environment  

3.7. Noise cleaning of the voice signal

4 ANALYSIS AND VISUALIZATION  OF THE CARDIAC ACOUSTIC BIOMEDICAL SIGNALS

4.1. Instrumental examinations in the diagnosis of cardiovascular diseases

4.1.1.  Cardiac auscultation

4.1.2.  Electrocardiography

4.1.3.  Phonocardiography

4.2. New digital technologies of heart sound processing

4.2.1.  Akustokardiograf hardware and software tools for recording and processing  signals of cardiac tones and murmurs

4.2.2.  Acousto cardiography

4.2.3.  AKUSTOKARD portal for remote processing of phonocardiograms

4.2.4.  Wavelet analysis of Korotkoff sounds

5 COMPUTER ANALYSIS OF LUNG SOUNDS  USING WAVELET TRANSFORM

5.1. Fourier transform-based spectral analysis of respiratory sounds  

5.2. Acquisition of images “visible sound” of the lungs  based on wavelet transform

5.2.1.  Acousto sonograms of audio files of records in the learning aids  “Auscultation of the lungs”

5.2.2.  Comparison of time-frequency resolution of acousto sonograms  and phono spirograms

5.3. Study of forced expiratory sounds

6 SPEECH SCRAMBLING IN COMMUNICATION CHANNELS

6.1. Scrambling of the voice signal  

6.2. Telephone conversation scrambling tools

6.2.1. Classification of speech scrambling equipment

6.2.2. Telephone encryptors of public network channels

6.2.3. Voice cryptoprotection equipment for cellular channels  

6.2.4. Voice protection levels

6.3. Testing the telephone encryptors  

6.3.1. Examples of testing the telephone encryptors  

6.3.2. Assessment of the quality of telephone encryptor vocoders

6.4. WAVELET-FONE voice signal scrambling system

6.4.1. Discrete-wavelet-transform-based scrambling algorithm  

6.4.2. Basic features of WAVELET-FONE System

7 TELEMEDICINE SYSTEMS WITH SCRAMBLING  OF ACOUSTIC BIOMEDICAL SIGNALS

7.1. Acousto-graphic study of heart and lung sounds

7.1.1. Acoustic signal recording hardware  

7.1.2. WaveView-MWA software

7.1.3. Examples of acousto sonograms of biomedical signals

7.2. AKUSTOKARD protected telemedicine system for remote detection of early stages of heart diseases

7.3. AKUSTOMED telemedicine system with preliminary  scrambling of biomedical signals

7.3.1. Protection of personal data confidentiality

7.3.2. Main features of the AKUSTOMED telemedicine system

7.3.3. Preliminary scrambling of biomedical signals 


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