Computational Ergodic Theory: 13 (Algorithms and Computation in Mathematics, 13) - Softcover

Choe, Geon Ho

Softcover

ISBN 10: 3642062075 ISBN 13: 9783642062070

Publisher: Springer, 2010

Synopsis

Ergodic theory is hard to study because it is based on measure theory, which is a technically difficult subject to master for ordinary students, especially for physics majors. Many of the examples are introduced from a different perspective than in other books and theoretical ideas can be gradually absorbed while doing computer experiments. Theoretically less prepared students can appreciate the deep theorems by doing various simulations. The computer experiments are simple but they have close ties with theoretical implications. Even the researchers in the field can benefit by checking their conjectures, which might have been regarded as unrealistic to be programmed easily, against numerical output using some of the ideas in the book. One last remark: The last chapter explains the relation between entropy and data compression, which belongs to information theory and not to ergodic theory. It will help students to gain an understanding of the digital technology that has shaped the modern information society.

About this title

About the Author

Geon Ho Choe is Emeritus Professor at Korea Advanced Institute of Science and Technology (KAIST). He obtained his PhD in Mathematics at the University of California, Berkeley, in 1987. In a career spanning several decades, he supervised 21 PhD students. He is the author of the books Computational Ergodic Theory (Springer, 2005) and Stochastic Analysis for Finance with Simulations (Springer, 2016). He received the 2022 Korean Mathematical Society Education Award.

From the Back Cover

Ergodic theory is hard to study because it is based on measure theory, which is a technically difficult subject to master for ordinary students, especially for physics majors. Many of the examples are introduced from a different perspective than in other books and theoretical ideas can be gradually absorbed while doing computer experiments. Theoretically less prepared students can appreciate the deep theorems by doing various simulations. The computer experiments are simple but they have close ties with theoretical implications. Even the researchers in the field can benefit by checking their conjectures, which might have been regarded as unrealistic to be programmed easily, against numerical output using some of the ideas in the book. One last remark: The last chapter explains the relation between entropy and data compression, which belongs to information theory and not to ergodic theory. It will help students to gain an understanding of the digital technology that has shaped the modern information society.

Edition details

• Publisher: Springer
• Publication date: 2010
• Language: English
• ISBN 10: 3642062075
• ISBN 13: 9783642062070
• Binding: Paperback
• Number of pages: 453