继续求物理书，物理资料，关于混沌理论的
混沌理論（Chaos theory）是在數學和物理學中，研究非線性系統在一定條件下表現出的「混沌」現象的理論。1963年美國氣象學家愛德華·羅倫茲提出混沌理論（Chaos），非線性系統具有的多樣性和多尺度性。混沌理論解釋了決定系統可能產生隨機結果。理論的最大的貢獻是用簡單的模型獲得明確的非周期結果。在氣象、航空及太空等領域的研究裡有重大的作用。
混沌理論認為在混沌系統中，初始條件十分微小的變化，經過不斷放大，對其未來狀態會造成極其巨大的差別。我們可以用在西方世界流傳的一首民謠對此作形象的說明。這首民謠說：
丟失一個釘子，壞了一隻蹄鐵；
壞了一隻蹄鐵，折了一匹戰馬；
折了一匹戰馬，傷了一位騎士；
傷了一位騎士，輸了一場戰鬥；
輸了一場戰鬥，亡了一個帝國。 非线性是混沌的基本条件 $m14$
建议不要找物理的
找些经典的数学书来看 原帖由 南宋无间道 于 2008-7-20 14:50 发表 http://www.dolc.de/forum/images/common/back.gif
非线性是混沌的基本条件 $m14$
建议不要找物理的
找些经典的数学书来看
能提供点关键词么？ 给你推荐一本书
http://www.amazon.com/Deterministic-Chaos-Heinz-Georg-Schuster/dp/3527293159
此书为chaos理论的经典教材，写书的是10年前chaos理论里的大牛。本人有形受此大牛的言传身教，可惜只学了个皮毛，惭愧惭愧。 http://books.google.com/books?id=9y2qSGpQR7QC&printsec=frontcover&dq=Deterministic+Chaos:+An+Introduction&sig=ACfU3U18v8-AXnusMZFyQJ-ERu7K0hI5yA
这里可以直接看，我晚上仔细看看
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Why not?The math books are more difficult. 原帖由 collboy 于 2008-7-21 11:00 发表 http://www.dolc.de/forum/images/common/back.gif
给你推荐一本书
http://www.amazon.com/Deterministic-Chaos-Heinz-Georg-Schuster/dp/3527293159
此书为chaos理论的经典教材，写书的是10年前chaos理论里的大牛。本人有形受此大牛的言传身教，可惜只学了个皮毛 ...
Yes, this is a nice book. But there are many other good books. 原帖由 orionsnow 于 2008-7-20 14:46 发表 http://www.dolc.de/forum/images/common/back.gif
混沌理論（Chaos theory）是在數學和物理學中，研究非線性系統在一定條件下表現出的「混沌」現象的理論。
1963年美國氣象學家愛德華·羅倫茲提出混沌理論（Chaos），非線性系統具有的多樣性和多尺度性。混沌理論解 ...
美國氣象學家愛德華·羅倫茲. He died about half a year ago. For LZ:
Perhaps you prefer math books. :) :)
Some suggestions: Dynamical systems theory, ODE, etc. ODE 我学过了， dynamical system 我也学过了。
后边的 PDE， 定性分析，范函分析，数值方法的这些我也学过了。
你说的这两本是数学物理方法的入门教材。 我想找的主要是非线性，多维（3维以上系统的）。
热力统计学我现在正在看。 看看还有什么好推荐的？ 可惜菜氏电路最终还是没有实际应用。貌似十年前就已经过气了。 原帖由 orionsnow 于 2008-7-22 22:24 发表 http://www.dolc.de/forum/images/common/back.gif
ODE 我学过了， dynamical system 我也学过了。
后边的 PDE， 定性分析，范函分析，数值方法的这些我也学过了。
你说的这两本是数学物理方法的入门教材。 我想找的主要是非线性，多维（3维以上系统的）。
热 ...
你学过了. Hehe. Perhaps this is good for you.
author = {K.T. Alligood and T.D. Sauer and J.A. Yorke},
title = {Chaos: An Introduction to Dynamical Systems},
publisher= {Springer, Berlin},
year = {2000},
It's better to choose one subject then, bifurcation, chaos etc.The bifurcations (local and global) in higher dimensional systems is not easy. The chaos is also difficult.
Complex systems? A nice review about "statistical mechanics of complex networks" in Review of Modern Physics. 原帖由 Bettencourt 于 2008-7-22 22:59 发表 http://www.dolc.de/forum/images/common/back.gif
可惜菜氏电路最终还是没有实际应用。貌似十年前就已经过气了。
No.
貌似生物学里头这个也有应用
Some nonlinear challenges in biologyLinkingservices der TIB/UB Hannover
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Author(s): Mosconi F (Mosconi, Francesco), Julou T (Julou, Thomas), Desprat N (Desprat, Nicolas), Sinha DK (Sinha, Deepak Kumar), Allemand JF (Allemand, Jean-Francois), Croquette V (Croquette, Vincent), Bensimon D (Bensimon, David)
Source: NONLINEARITY Volume: 21 Issue: 8 Pages: T131-T147 Published: AUG 2008
Times Cited: 0 References: 71 Citation MapCitation Map beta
Abstract: Driven by a deluge of data, biology is undergoing a transition to a more quantitative science. Making sense of the data, building new models, asking the right questions and designing smart experiments to answer them are becoming ever more relevant. In this endeavour, nonlinear approaches can play a fundamental role. The biochemical reactions that underlie life are very often nonlinear. The functional features exhibited by biological systems at all levels (from the activity of an enzyme to the organization of a colony of ants, via the development of an organism or a functional module like the one responsible for chemotaxis in bacteria) are dynamically robust. They are often unaffected by order of magnitude variations in the dynamical parameters, in the number or concentrations of actors (molecules, cells, organisms) or external inputs (food, temperature, pH, etc). This type of structural robustness is also a common feature of nonlinear systems, exemplified by the fundamental role played by dynamical fixed points and attractors and by the use of generic equations (logistic map, Fisher-Kolmogorov equation, the Stefan problem, etc.) in the study of a plethora of nonlinear phenomena. However, biological systems differ from these examples in two important ways: the intrinsic stochasticity arising from the often very small number of actors and the role played by evolution. On an evolutionary time scale, nothing in biology is frozen. The systems observed today have evolved from solutions adopted in the past and they will have to adapt in response to future conditions. The evolvability of biological system uniquely characterizes them and is central to biology. As the great biologist T Dobzhansky once wrote: 'nothing in biology makes sense except in the light of evolution'. LZ好上进。
$送花$ 最近在看图灵的老文章，关于化学计算机的 http://emuch.net/bbs
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