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 a scholar and researcher working in the areas of Artificial Intelligence, Machine Learning, and Data Analytics, and concentrates on applied and interdisciplinary research. She holds a doctorate and is presently working at Chandigarh University, Punjab, India, where she has been active in teaching, research, and curriculum development. She has more than 12 years of experience teaching undergraduate and postgraduate students in computer science and computer applications. Dr. Mishra is an author of several research published papers for reputed IEEE conferences and international journals in various fields, including Deep Learning, Image Processing, and Machine Learning. Her work focuses on practical deployment, model analysis, and the solution of real-life problems with the help of the current AI methods. She has also directed student projects and research work in line with the modern trends in the industry and academics. Her fields of expertise are Deep Learning, Machine Learning, Image Processing, and Computing in MATLAB. She has worked as a teacher in 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).