Chen's attractor family and Rossler attractor family are two types of attractors that are being compared in this document. The document notes there is a parallel gradual change process between the two families that is interesting and asks if there are any underlying connections between them or possibilities for other extensions.
Chen's attractor family and Rossler attractor family are two types of attractors that are being compared in this document. The document notes there is a parallel gradual change process between the two families that is interesting and asks if there are any underlying connections between them or possibilities for other extensions.
This document discusses attractors and dynamical systems through examples like number games and the Lorenz system. It begins by using a 3-digit number game to illustrate the concept of attractors, showing how different starting numbers eventually converge to the fixed point attractors of 495 and 000. The document then discusses how this idea can be applied in other contexts like numerical analysis, economics, and system identification. It also introduces different types of attractors like fixed points, periodic attractors, and strange attractors. Finally, it summarizes recent work extending the Lorenz system to a one-parameter family and exploring relationships between different 3D autonomous systems.
The document discusses generalized distributions and the central limit theorem. It begins by covering the normal distribution and how the central limit theorem explains why it is so common. It then discusses power law distributions and how they are more common in complex systems. The generalized central limit theorem states that the sum of random variables with power law distributions will tend towards a stable distribution. Stable distributions include the normal distribution as a special case and exhibit power law behavior for large values.
This document summarizes recent discoveries and challenges in chaos theory presented by Xiong Wang from the Centre for Chaos and Complex Networks at City University of Hong Kong. Some key points discussed include: discovering a chaotic system with one stable equilibrium point, using symmetry to create systems with multiple equilibria whose stability can be tuned, and open questions around reconciling local stability with global chaotic behavior. The document concludes by acknowledging that chaos is a global phenomenon not precluded by local stability near equilibria.
This document is a lecture on the concept of mass in Newtonian mechanics and Lagrangian mechanics. It begins with an introduction that defines physics as the study of matter, space-time and motion. It then discusses mass as a way to model matter. The lecture will cover the concept of mass in Newtonian mechanics, including inertia mass, gravitational mass and others. It will also discuss mass in Lagrangian mechanics. The goal is to see how the understanding of mass has developed over time through different theories.
The document discusses challenging implicit assumptions in physics, such as differentiability. It argues that general relativity is incomplete because it only considers differentiable coordinate transformations, rather than arbitrary transformations. Quantum phenomena like uncertainty and non-commutativity could emerge from spacetime non-differentiability. The author proposes a complete theory with non-differentiable spacetime where physical laws remain valid under differentiable or non-differentiable transformations, reconciling quantum effects.
This document discusses discoveries and challenges in chaos theory. It begins by asking basic questions about the mechanisms that generate chaos and the types of systems that can exhibit chaotic dynamics. It then discusses concepts like equilibria, Jacobian matrices, Hartman-Grobman and Shilnikov theorems as they relate to the stability of equilibria and generation of chaos. Examples of chaotic systems like Lorenz, Chen and Rossler are provided. The document finds a chaotic system with one stable equilibrium, then extends this finding to systems with no equilibria, two equilibria and tunable stability. It concludes that chaos is a global phenomenon while local stability exists near equilibria.
Above under and beyond brownian motion talkXiong Wang
This talk was Dedicated to Einstein's miracle year at his 26
以此次讲座,致敬当年爱因斯坦26岁时的几篇牛文之一,对布朗运动的研究。
对随机游走的研究,已经取得了很深入的进展,本次讲座从布朗运动模型入手,逐步深入,引入分数阶布朗运动,levy随机飞行等概念
这些模型在各种复杂系统中非常常见,比如金融市场,网络交通流量等等,
会简略介绍这些模型在金融系统的应用,以及分析基于布朗运动随机游走的金融模型的弊端
给大家一个随机游走世界的全景
Xiong Wang studied the relationship between chaotic dynamical systems and the stability of equilibria. Wang presents a three-dimensional system with one stable equilibrium that exhibits chaotic behavior for certain parameter values, as shown by a positive largest Lyapunov exponent and bifurcation diagram. This contrasts with previous systems that generate chaos via unstable equilibria. Open questions remain about rigorously proving chaos and the coexistence of the stable point attractor and strange attractor.
This document discusses attractors and dynamical systems through examples like number games and the Lorenz system. It begins by using a 3-digit number game to illustrate the concept of attractors, showing how different starting numbers eventually converge to the fixed point attractors of 495 and 000. The document then discusses how this idea can be applied in other contexts like numerical analysis, economics, and system identification. It also introduces different types of attractors like fixed points, periodic attractors, and strange attractors. Finally, it summarizes recent work extending the Lorenz system to a one-parameter family and exploring relationships between different 3D autonomous systems.
The document discusses generalized distributions and the central limit theorem. It begins by covering the normal distribution and how the central limit theorem explains why it is so common. It then discusses power law distributions and how they are more common in complex systems. The generalized central limit theorem states that the sum of random variables with power law distributions will tend towards a stable distribution. Stable distributions include the normal distribution as a special case and exhibit power law behavior for large values.
This document summarizes recent discoveries and challenges in chaos theory presented by Xiong Wang from the Centre for Chaos and Complex Networks at City University of Hong Kong. Some key points discussed include: discovering a chaotic system with one stable equilibrium point, using symmetry to create systems with multiple equilibria whose stability can be tuned, and open questions around reconciling local stability with global chaotic behavior. The document concludes by acknowledging that chaos is a global phenomenon not precluded by local stability near equilibria.
This document is a lecture on the concept of mass in Newtonian mechanics and Lagrangian mechanics. It begins with an introduction that defines physics as the study of matter, space-time and motion. It then discusses mass as a way to model matter. The lecture will cover the concept of mass in Newtonian mechanics, including inertia mass, gravitational mass and others. It will also discuss mass in Lagrangian mechanics. The goal is to see how the understanding of mass has developed over time through different theories.
The document discusses challenging implicit assumptions in physics, such as differentiability. It argues that general relativity is incomplete because it only considers differentiable coordinate transformations, rather than arbitrary transformations. Quantum phenomena like uncertainty and non-commutativity could emerge from spacetime non-differentiability. The author proposes a complete theory with non-differentiable spacetime where physical laws remain valid under differentiable or non-differentiable transformations, reconciling quantum effects.
This document discusses discoveries and challenges in chaos theory. It begins by asking basic questions about the mechanisms that generate chaos and the types of systems that can exhibit chaotic dynamics. It then discusses concepts like equilibria, Jacobian matrices, Hartman-Grobman and Shilnikov theorems as they relate to the stability of equilibria and generation of chaos. Examples of chaotic systems like Lorenz, Chen and Rossler are provided. The document finds a chaotic system with one stable equilibrium, then extends this finding to systems with no equilibria, two equilibria and tunable stability. It concludes that chaos is a global phenomenon while local stability exists near equilibria.
Above under and beyond brownian motion talkXiong Wang
This talk was Dedicated to Einstein's miracle year at his 26
以此次讲座,致敬当年爱因斯坦26岁时的几篇牛文之一,对布朗运动的研究。
对随机游走的研究,已经取得了很深入的进展,本次讲座从布朗运动模型入手,逐步深入,引入分数阶布朗运动,levy随机飞行等概念
这些模型在各种复杂系统中非常常见,比如金融市场,网络交通流量等等,
会简略介绍这些模型在金融系统的应用,以及分析基于布朗运动随机游走的金融模型的弊端
给大家一个随机游走世界的全景
Xiong Wang studied the relationship between chaotic dynamical systems and the stability of equilibria. Wang presents a three-dimensional system with one stable equilibrium that exhibits chaotic behavior for certain parameter values, as shown by a positive largest Lyapunov exponent and bifurcation diagram. This contrasts with previous systems that generate chaos via unstable equilibria. Open questions remain about rigorously proving chaos and the coexistence of the stable point attractor and strange attractor.
12. 突破可微性才有的玩,
比如布朗运动
The Wiener process Wt is characterized by three properties:[1]
1.W0 = 0
2.The function t → Wt is almost surely continuous
3.Wt has independent increments with (for 0 ≤ s < t).
N(μ, σ2) denotes the normal distribution with expected value μ and variance σ2.
如果 Wt 是布朗运动,那么 也是一个布朗运动
12