Random Signal Processing: 1st Edition (Paperback) book cover

Random Signal Processing

1st Edition

By Shaila Dinkar Apte

CRC Press

440 pages | 40 B/W Illus.

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Paperback: 9781138746275
pub: 2017-08-22
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pub: 2017-08-18
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This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral density and power spectral density. The properties of random processes and signal modelling are discussed with basic communication theory estimation and detection. MATLAB simulations are included for each concept with output of the program with case studies and project ideas. The chapters progressively introduce and explain the concepts of random signals and cover multiple applications for signal processing.

The book is designed to cater to a wide audience starting from the undergraduates (electronics, electrical, instrumentation, computer, and telecommunication engineering) to the researchers working in the pertinent fields.

Key Features:

• Aimed at random signal processing with parametric signal processing-using appropriate segment size.

• Covers speech, image, medical images, EEG and ECG signal processing.

• Reviews optimal detection and estimation.

• Discusses parametric modeling and signal processing in transform domain.

• Includes MATLAB codes and relevant exercises, case studies and solved examples including multiple choice questions

Table of Contents

Introduction to Random Signals

1.1Introduction to Set Theory


1.3 Random Variable

1.4 Standard Distribution Functions

1.5 Central Limit Theorem, Chi square test, K-S test


Multiple-Choice Questions

Review Questions


Properties of Random Variables

2.1 Statistical Properties of Random Variables

2.2 Functions for Finding Moments

2.3 Transformations of a Random Variable

2.4 Computation of Energy density Spectrum of deterministic signal


Multiple-Choice Questions

Review Questions


Multiple Random Variables and Random Process

3.1 Multiple Random Variables

3.2 Modelling a Random Signal

3.3 Random Processes


Multiple-Choice Questions

Review Questions



4.1 Basis of Communication Theory

4.2 LTV Systems

4.3 Optimum Detection

4.4 Estimation Theory


Multiple-Choice Questions

Review Questions

Fundamentals of Speech Processing

5.1 LTI and LTV Model for Speech Production

5.2 Voiced and Unvoiced Decision Making

5.3 Audio file formats-Nature of .wav File

5.4 Extraction of Fundamental Frequency

5.5 Formants and relation of formants with LPC

5.6 Evaluation of Formants

5.7 Evaluation of MFCC

5.8 Evaluation of LPC


Multiple-Choice Questions

Review Questions


Spectral Estimation of Random Signals

6.1 Estimation of Density Spectrum

6.2 Non-parametric methods

6.3 Parametric Methods

6.4 Other Spectral Estimation Methods

6.5 Evaluation of Formants using Power Spectral Density estimate

6.6 Evaluation of Cepstrum

6.7 Evaluation of Higher Order Spectra


Multiple Choice Questions

Review Questions



Statistical Speech processing

7.1 Measurement of Statistical parameters of Speech

7.2 Dynamic Time Warping

7.3 Statistical Sequence Recognition for ASR

7.4 Statistical Pattern Recognition and Parameter Estimation

7.5 VQ-HMM based Speech Recognition

7.6 Discriminant Acoustic Probability Estimation


Multiple-Choice Questions

Review Questions



Transform Domain Speech Processing

8.1 Short Segment Analysis of Speech

8.2 Use of Transforms for Speech Processing

8.3 Applications of DCT for Speech Processing

8.4 Short Time Fourier Transform (STFT)

8.5 Wavelet Transform

8.6 Haar Wavelet & multiresolution analysis

8.7 Daubechies Wavelets

8.8 Some other standard wavelets

8.9 Applications of wavelet transform


Multiple Choice Questions

Review Questions


Image Processing Techniques

9.1 Image Representation and Spatial Filtering

9.2 Transformations on Image

9.3 Histogram Equalization

9.4 Transform Domain Image Processing


Multiple Choice Questions

Review Questions


Applications of Random Signal Processing

10.1 Case Study 1: Handwritten Character Recognition

10.2 Case Study 2: Writer identification and verification

About the Author

Dr. Shaila Dinkar Apte is currently working as a professor on PG side in Rajarshi Shahu College of Engineering, Pune and as reviewer for the International Journal of Speech Technology by Springer Publication, International Journal of Digital Signal Processing, Elsevier Publication. She is currently guiding 5 Ph.D. candidates. Eight candidates have completed their Ph.D. under her guidance. About 70 candidates completed their M.E. dissertations under her guidance. Almost all dissertations are in the area of signal processing. She has a vast teaching experience of 35 years in electronics engineering, and enjoys great popularity amongst students. She has been teaching Digital Signal Processing and Advanced Digital Signal Processing since last 22 years. Her previous designations include being an Assistant Professor in Walchand College of Engineering, Sangli, for 27 years; a member of board of studies for Shivaji University and a principle investigator for a research project sponsored by ARDE, New Delhi.

Dr. Shaila Dinkar Apte completed her M. Sc. (Electronics) from Mumbai University in 1976 and acquired the first rank. She then received her M.E. (Electronics) in 1991 from Walchand College of Engineering, Sangli and Ph.D. in 2001 in Electronics Engineering from Walchand College of Engineering, under Shivaji University, Kolhapur. Her Ph.D. thesis involved work on speaker modeling using optimal mother wavelet.

She has published 28 papers in reputed international journals, more than 40 papers in international conferences and about 15 papers in national conferences. She has a patent granted to her credit related to generation of mother wavelet from speech signal. Indian patent related to emotional speech synthesis is published. A book titled "Digital Signal Processing", "Advanced Digital Signal Processing" and "Speech and Audio Processing" are published by Wiley India. A second reprint of second edition of the first book is in the market. A book titled "Signals and Systems-Principles and applications" is published by Cambridge university press. Her areas of interest include emotional speech synthesis, emotion detection and context based personalized speech synthesis.

Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General