Bounded Noises in Physics, Biology, and Engineering
The second is devoted to framing bounded noises in the theory of random dynamical systems and random bifurcations, while the third is devoted to applications of bounded stochastic processes in biology, one of the major areas of potential applications of this subject. The final part concerns the appl...
| Other Authors: | |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
New York, NY
Birkhäuser
2013, 2013
|
| Edition: | 1st ed. 2013 |
| Series: | Modeling and Simulation in Science, Engineering and Technology
|
| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Introduction
- Part I : Modeling of Bounded Noises and Their Applications in Physics
- On Bounded Stochastic Processes
- Dynamics of Systems With Randomly Disordered Periodic Excitations
- Noise-Induced Phenomena: Effects of Noises Based on Tsallis Statistics
- Dynamical Systems Driven by Dichotomous Noise
- Stochastic Oscillator : Brownian Motion With Adhesion
- Numerical Study of Energetic Stability For Harmonic Oscillator With Fluctuating Damping Parameter
- A Moment-Based Approach to Bounded Non-Gaussian Colored Noise
- Spatiotemporal Bounded Noises, and Their Application to the Ginzburg-Landau Equation
- Part II: Bounded Noises in the Framework of Discrete and Continuous Random Dynamical Systems
- Bifurcations of Random Differential Equations With Bounded Noise
- Effects of Bounded Random Perturbations on Discrete Dynamical Systems
- Part III: Bounded Stochastic Fluctuations in Biology
- Bounded Stochastic Perturbations May Induce Non-Genetic Resistance to Anti-Tumor Chemotherapy
- Interplay Between Cross Correlation and Delays in the Sine-Wienernoise-Induced Transitions
- Bounded Extrinsic Noises Affecting Biochemical Networks With Low Molecule Numbers
- Part IV: Bounded Noises: Applications in Engineering
- Almost Sure Stability of Fractional Viscoelastic Systems Driven By Bounded Noises
- Model Selection for Random Functions With Bounded Range. Applications in Science and Engineering
- From Model-Based to Data-Driven Filter Design