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Digital Signal Processing: Illustration Using Python

Autor S Esakkirajan, T Veerakumar, Badri N Subudhi
en Limba Engleză Paperback – 26 ian 2024
Digital signal processing deals with extraction of useful information from signals. Signal processing algorithms help observe, analyse and transform signals.  The objective of this book is to develop signal processing algorithms using Python. Python is an interpreted, object-oriented high-level programming language widely used in various software development fields such as data science, machine learning, web development and more.
Digital Signal Laboratory is playing an important role in realizing signal processing algorithms, utilizing different software solutions. The intention of this textbook is to implement signal processing algorithms using Python. Since Python is an open-source language, students, researchers, and faculty can install and work with it without spending money, reducing the financial burden on institutions. Each chapter in this book begins with prelab questions, a set of Python examples to illustrate the concepts, exercises to strengthen the understanding of the concepts, and objective questions to help students prepare for competitive examinations.   
This book serves as an undergraduate textbook, it can be used for individual study, and it can also be used as the textbook for related courses.


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Specificații

ISBN-13: 9789819967513
ISBN-10: 9819967511
Pagini: 523
Ilustrații: XVIII, 523 p. 1 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.75 kg
Ediția:1st ed. 2024
Editura: Springer Nature Singapore
Colecția Springer
Locul publicării:Singapore, Singapore

Cuprins

CHAPTER 1: Generation of Continuous-Time Signals.- CHAPTER 2: Sampling and Quantization of Signals.-CHAPTER 3: Generation and Operation on Discrete-Time Sequence.- CHAPTER 4: Discrete-Time Systems.-CHAPTER 5: Transforms.-CHAPTER 6: Filter Design using Pole-Zero Placement Method-CHAPTER 7: FIR Filter Design-CHAPTER 8: Infinite Impulse Response Filter-CHAPTER 9: Effect of Quantization of Filter Coefficients-CHAPTER 10: Multi-rate Signal Processing-CHAPTER 11: Adaptive Signal Processing Case Studies

Notă biografică

S. Esakkirajan is working as Professor in the Department of
Instrumentation and Control Systems Engineering, PSG College of Technology,
Coimbatore. He has twenty years of teaching experience. He has guided four
research scholars in the area of signal and image processing. He has published
Digital Signal Processing and Digital Image Processing text books published by
McGraw Hill. He was the organizing secretary of IEEE International Conference
on “Machine Vision and Image Processing” in the year 2012. He has published
papers in the field of signal and image processing in reputed journals and
conferences. 
T. Veerakumar is an Associate Professor in the Department of
Electronics and Communication Engineering, National Institute of Technology,
Goa. He graduated with a B.E. in Electronics and Communication Engineering from
RVS College of Engineering Technology, Dindigul. Then, he did an M.E. degree in
Applied Electronics from PSG College of Technology, Coimbatore, and a Ph.D. in
Image Denoising from Anna University, Chennai. He co-authored the Text Book
titled “Digital Image Processing” and “Digital Signal Processing,” published by
Tata McGraw Hill. In addition, he has published around 60 research articles in
reputed Journals and Conferences. His area of interest includes Signal and Image Processing, Biomedical Image Processing, Object Detection, and Tracking.
Badri Narayan Subudhi received M.Tech. in
Electronics and System Communication from National Institute of Technology,
Rourkela, India, in 2008-09. He worked for his PhD from Machine Intelligence
Unit, Indian Statistical Institute, Kolkata, India in year 2014 (degree from
Jadavpur University). Currently he is serving as an Assistant Professor at
Indian Institute of Technology Jammu, India. Prior to this he was working as an
Assistant Professor at NIT Goa fromJuly 2014 to March 2017. He received CSIR
senior research fellowship for the year 2011-2015. He was nominated as the
Young Scientist Awardees by Indian Science Congress Association for the year
2012-2013. He was awarded with Young Scientist Travel grant award from DST,
Government of India and Council of Scientific and Industrial Research, India in
the year 2011. He is the recipient of Bose-Ramagnosi Award for the year 2010
from DST, Government of India under India-Trento Programme for Advanced
Research (ITPAR). He was a visiting scientist at University of Trento, Italy
during Aug. 2010 to Feb 2011. His research interests include Video Processing,
Image Processing, Medical Image Processing, Machine Learning, Pattern Recognition, and Remote Sensing Image Analysis. He co-authored the Text Book
titled “Digital Signal Processing,” published by Tata McGraw Hill. He has
published around 80 research papers in reputed journals and conferences. He is
a senior member IEEE.



Textul de pe ultima copertă

Digital signal processing deals with extraction of useful information from signals. Signal processing algorithms help observe, analyse and transform signals.  The objective of this book is to develop signal processing algorithms using Python. Python is an interpreted, object-oriented high-level programming language widely used in various software development fields such as data science, machine learning, web development and more. Digital Signal Laboratory is playing an important role in realizing signal processing algorithms, utilizing different software solutions. The intention of this textbook is to implement signal processing algorithms using Python. Since Python is an open-source language, students, researchers, and faculty can install and work with it without spending money, reducing the financial burden on institutions. Each chapter in this book begins with prelab questions, a set of Python examples to illustrate the concepts, exercises to strengthen the understanding of the concepts, and objective questions to help students prepare for competitive examinations.   
This book serves as an undergraduate textbook, it can be used for individual study, and it can also be used as the textbook for related courses.

Caracteristici

Presents illustrations of signal processing algorithms using Python. Gives detailed inferences for each experiment. Provides case studies that include speech signal analysis, power line signal analysis, analysis of vibration.