AI Foundations and Applications with MATLAB

Erscheinungsjahr 2025
ISBN: 978-3-031-84422-5
Verlag: Springer

Buch, Englisch, 673 Seiten, Format (B × H): 155 mm x 235 mm

This textbook provides fundamentals and practical skills on AI foundations and applications with two MATLAB programming modes. It includes twelve chapters with detailed introductions for the foundation knowledge of AI, structures, key components, and hands-on AI projects implemented in various applications in our world.

Unlike other AI related textbooks, in which the Python is used, the MATLAB is adopted in this textbook. The Python programming mode builds AI projects with functions involving huge blocks of codes, which is a difficult task. However, in MATLAB mode, provides two programming styles, Apps, and function library. The Apps graphical user interface (GUIs) assist users, especially the beginners, to learn and build AI projects with no coding lines quickly and easily. To compensate the possible code-hiding in Apps, MATLAB provides a Converting Codes function to allow users to convert those Apps to the related codes. It enables users to have a clear picture between Apps and detailed coding process. The function library enables users to build AI projects with detailed codes. This textbook also includes homework questions, exercises, lab projects and case studies.

This book is designed as a textbook for advanced-level students in Computer Science or Computer Engineering. Also, AI engineers, who have an interest in learning and developing professional AI applications to solve real problems in the world will want to purchase this book.

Zielgruppe

Graduate

Autoren/Hrsg.

Bai, Ying

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

Chapter 1 Introduction.- Chapter 2 Learning and Decision Making Process.- Chapter 3 Fuzzy Logic Inference System.- Chapter 4 Introduction to Machine Learning.- Chapter 5 Introduction to Regression Algorithms.- Chapter 6 Introduction to Classification Algorithms.- Chapter 7 Neural Networks and Deep Learning.- Chapter 8 Introduction to Unsupervised Learning.- Chapter 9 Introduction to Reinforcement Learning.- Chapter 10 Introduction to Adaptive Neuro Fuzzy Inference System.- Chapter 11 Case Study Projects on Fuzzy Logic Technology.- Chapter 12 Case Study Projects on Deep Learning.- Appendix A.

Über Autor(innen)

Dr. YING BAI is a Professor in the Department of Computer Science and Engineering at Johnson C. Smith University located at Charlotte, North Carolina. His special interests include: Artificial intelligence, soft-computing, database programming, fuzzy logic controls, automatic and robots controls, as well as robots calibrations. His industry experience includes positions as software and senior software engineers at companies such as Motorola MMS, Schlumberger ATE Technology, Immix TeleCom, and Lam Research. Since 2003, Dr. Bai has published 20 books with publishers such as Prentice Hall, CRC Press LLC, Springer, Cambridge University Press and Wiley IEEE Press. He also published more than 70 academic research papers in IEEE Trans. journals and international conferences. Most books are about the micro-controller control and programming, fuzzy logic implementations, classical and modern controls, cross-language interface programming, database programming and applications.