Mathematical Structures for Intelligent

Mathematical Structures for Intelligent Algorithmic Design in Modern Computing presents a systematic exploration of the mathematical foundations that underpin intelligent algorithms used in today’s computational systems. The book examines key structures such as linear algebra, graph theory, probability, optimization, and discrete mathematics, showing how they shape the design, analysis, and performance of modern algorithms. It emphasizes the role of mathematical abstraction in developing efficient, scalable, and reliable solutions for complex problems in artificial intelligence, data science, machine learning, and high-performance computing. By linking theory with practical algorithmic strategies, the book enables readers to understand why certain algorithms work, how they can be improved, and how new intelligent methods can be constructed. It serves as a valuable resource for students, researchers, and professionals seeking a deeper mathematical perspective on intelligent computing systems.