We present a neural model for a singular-continuous nowhere-differentiable (SCND) attractors. This model shows various characteristics originated in attractor's nowhere-differentiability, in spite of a differentiable dynamical system. SCND attractors are still unfamiliar in the neural network studie
Nowhere-differentiable attractors
β Scribed by O. E. Rossler; C. Knudsen; J. L. Hudson; I. Tsuda
- Publisher
- John Wiley and Sons
- Year
- 1995
- Tongue
- English
- Weight
- 566 KB
- Volume
- 10
- Category
- Article
- ISSN
- 0884-8173
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β¦ Synopsis
The notion of nowhere-differentiable attractors is illustrated with four prototype equations, that is, maps of invertible type. Four classes of nowhere-differentiable attractors can be distinguished so far: the (nongeneric) continuous-nonchaotic-nonfractal type; the (nongeneric) continuous-fractal type; the (generic) singular-continuous-fractal type; and the (generic) continuous-fractal-in-a-projection type. The history of all four classes is linked with the name of J. A. Yorke in different ways. Even though continuous fractal nowhere-differentiable attractors do not exist generically, the hypothesis that the fractal geometry of nature may be a consequence of the fact that nature is a differentiable dynamical system is strengthened. Attractors with nowhere-differentiable generic projections can mimic the whole richness of fractal pictures.
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