Computational Ergodic Theory

· Algorithms and Computation in Mathematics 13권 · Springer Science & Business Media
eBook
453
페이지
검증되지 않은 평점과 리뷰입니다.  자세히 알아보기

eBook 정보

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.

이 eBook 평가

의견을 알려주세요.

읽기 정보

스마트폰 및 태블릿
AndroidiPad/iPhoneGoogle Play 북 앱을 설치하세요. 계정과 자동으로 동기화되어 어디서나 온라인 또는 오프라인으로 책을 읽을 수 있습니다.
노트북 및 컴퓨터
컴퓨터의 웹브라우저를 사용하여 Google Play에서 구매한 오디오북을 들을 수 있습니다.
eReader 및 기타 기기
Kobo eReader 등의 eBook 리더기에서 읽으려면 파일을 다운로드하여 기기로 전송해야 합니다. 지원되는 eBook 리더기로 파일을 전송하려면 고객센터에서 자세한 안내를 따르세요.