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This book is a complete, industry-driven text to teach readers practical MATLAB skills in engineering, data analysis, automation, modeling, and simulation, as well as the ability to build intelligent systems. From practical workflows to hands-on examples and industry applications, the book fills the gap between theory learning using MATLAB and application in the engineering lab.
Starting from the basics of MATLAB, the book then shifts its focus toward the latest technologies in engineering: signal processing, image processing, machine learning, automation, working with Simulink units and system design, and finally to hardware integration, data preprocessing, and data visualization. Fundamental engineering principles and implementation-oriented examples using MATLAB code are introduced in each chapter to simulate real industrial situations.
Readers are provided with a set of directions on how to read, pre-process data, create scalable MATLAB programs, visualize engineering data, automate repetitive processes, and create mathematical models and simulation models. The book provides a good introduction to how machine learning techniques can be used in engineering applications. The book also covers advanced topics such as time-series analysis, image processing, workflow optimization, real-time system modeling, and interfacing with hardware using Arduino and Raspberry Pi.
The book is unique in focusing on problems, practical applications to the actual world, and scalability of engineering procedures compared to syntax-focused MATLAB books. The book provides practical guidelines for students, researchers, engineers, and professionals who want to use MATLAB for applied engineering, academic study, industry control, and automation in today's engineering environment.
What You Will Learn:
· Gain an understanding of the basics of MATLAB and typical engineering practices
· Write efficient and scalable MATLAB programs
· Dig into real-life data import, data cleaning, data pre-processing, and data analysis
· Develop engineering drawings, renderings, and reports in 2D and 3D professional formats
· Develop mathematical modeling and engineering simulations
· Use optimization and computational skills numerically
· Analyze time-series data and perform signal processing
· Build up image processing and computer vision programs
· Apply workflows for machine learning and data analytics to MATLAB
· Simplify engineering tasks and streamline computational processes
· Model and simulate a system using Simulink
· Connect MATLAB to hardware platforms, IoT systems, APIs, and other applications
Who This Book Is for:
Beginning-Intermediate engineering students (undergraduate and postgraduate) and professionals (such as data analysts) who want to build their skills to use MATLAB for practical, real-world engineering workflows, data analysis, modeling, automation, simulation, machine learning, and hardware integration as well as intelligent data-driven applcations
Dr. Komal Mishra is an Artificial Intelligence and Machine Learning specialist, researcher, and scholar specializing in deep learning, image processing, data analytics, machine learning, and artificial intelligence. Currently, she is associated with Chandigarh University, Punjab, India where she is actively engaged in teaching, research, and curriculum development. Having been in the academic field for more than 12 years, she has taught computer applications and science to both undergraduate and postgraduate students. Dr. Mishra has published several research papers in various IEEE conferences and international journals. Her research interests lie in the application of AI techniques and real-world problem solving using modern computational approaches. She has supervised a number of student projects and research works which were market-oriented or covered trends in the academic field. Her areas of expertise are deep learning, image processing, data analytics, machine learning, and MATLAB-based computing. She has been a teacher of Python programming, data structures, artificial intelligence, machine learning, and MATLAB.
Keshav Kumar is pursuing his PhD in Hardware Security from Lingaya's Vidyapeeth (university), Faridabad, Haryana, India and is also working as an Assistant Professor in the Department of Electronics and Communication Engineering, Pranveer Singh Institute of Technology Kanpur, India. He also has worked with Cha University, Punjab, India (NIRF 29). He has completed his Master of Engineering in ECE with a specialization in Hardware Security from Chitkara University, Punjab, India. He has also worked as a JRF with NIT Patna and as an Assistant Lecturer at Chitkara University, Punjab, India. Keshav has authored and co-authored three books with CRC Press and Taylor & Francis, and another book with Nova Science. He has written more than 45 research papers in the fields of hardware security, green communication, low-power VLSI design, machine learning techniques, and IoT. He also has worked with professors from 20 countries. His areas of specialization include deep learning, hardware security, green communication, low-power VLSI design, machine learning techniques, WSN, and IoT. Keshav has experience teaching Python programming, embedded systems, IoT, computer networks, and digital electronics. He is also associated with Gyancity Research Consultancy Pvt Ltd. He is a member of IAENG. And he has approximatey 600 citations (Google Scholar), 14 H-index (Google Scholar), and 11 H-Index (Scopus).
| Publication Date: | 25 December 2026 |
| Publisher: | Apress |
| Imprint: | Apress |
| ISBN-13: | 9798868830037 |
| Format: | Paperback softback |