Название: Mathematical Modeling for Computer Applications
Автор: Biswadip Basu Mallik, M. Niranjanamurthy, Sharmistha Ghosh, Valentina Emilia Balas, Krishanu Deyasi, Santanu Das
Издательство: Wiley-Scrivener
Серия: Mathematics and Computer Science
Год: 2024
Страниц: 546
Язык: английский
Формат: pdf (true)
Размер: 46.1 MB

This new volume in this groundbreaking series on mathematics and computer science builds on the basic concepts and fundamentals laid out in previous volumes, presenting the reader with more advanced and cutting-edge topics being developed in this exciting field.

Description:
The mathematical sciences are part of nearly all aspects of everyday life. The discipline has underpinned such beneficial modern capabilities as internet searches, medical imaging, computer animation, numerical weather predictions, and all types of digital communications. This outstanding new volume in the series, “Mathematics and Computer Science,” examines the current state of mathematical science and explores the changes needed for the discipline to be in a strong position and able to maximize its contributions.

Besides covering important practical applications for the areas where mathematics and Computer Science intersect, the editors of this new volume recommend that training for future generations of mathematical scientists should be re-assessed in light of the increasingly cross-disciplinary nature of the mathematical sciences. In addition, because of the valuable interplay between ideas and people from all parts of the mathematical sciences, this group of curated papers emphasizes that universities and governments need to continue to invest in the full spectrum of the mathematical sciences in order for the whole enterprise to continue to flourish long-term. Emphasis on important developments in applied mathematics and modeling, analysis and its applications, applied algebra and its applications, geometry and its applications, algebraic statistics and its applications as well as algebraic topology and its applications are covered. Whether for the veteran engineer, new hire, or student, this is a must-have volume for any library.

Mathematics is the foundation on which Computer Science is built. Mathematical Logic, Set theory, Combinatorics, Graph Theory, Probability Theory, Number Theory, and Algebra are all part of Discrete Mathematics and form the basic foundation for Programming and Computer Science. Analytical skills are a necessity for learning problem-solving and data analysis. And, mathematics is the first place where you get to use these skills. Computer science examines the principles and use of computers in processing information, designing hardware and software, and using applications. Algebra is used in computer science in the development of algorithms and software for working with mathematical objects. It is also used to design formulas that are used in numerical programs and for complete scientific computations.

Statistics is a form of mathematics used in Computer Science that uses quantified models, representations, and synopses for a provided collection of experimental data or actual studies. The field studies methodologies to obtain, review, evaluate, and form conclusions from data. Statistics is used for data mining, speech recognition, vision and image analysis, data compression, traffic modelling, and even Artificial Intelligence (AI) and for simulations. Calculus is also used in an array of computer science areas, including creating graphs or visuals, simulations, problem-solving applications, coding in applications, creating statistic solvers, and the design and analysis of algorithms. Thus, Mathematics and Computer Science go hand in hand and in this volume entitled “Mathematical Modeling for Computer Applications”, we focus on the integration of mathematics and Computer Science for scientific and engineering applications.

Audience:
Engineers, scientists, researchers, developers, faculty, and students in Computer Science and engineering, electronics, communication engineering, and information technology.








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