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The recent demonstration of neuromorphic computing with spin-torque nano-oscillators has opened a path to energy efficient data processing. The success of this demonstration hinged on the intrinsic short-term memory of the oscillators. In…

We focus on emergence of the power-law cross-correlations from processes with both short and long term memory properties. In the case of correlated error-terms, the power-law decay of the cross-correlation function comes automatically with…

Methodology · Statistics 2014-12-11 Ladislav Kristoufek

We study the dynamics of the Forced Logistic Map in the cylinder. We compute a bifurcation diagram in terms of the dynamics of the attracting set. Different properties of the attracting set are considered, as the Lyapunov exponent and, in…

Dynamical Systems · Mathematics 2011-12-20 Angel Jorba , Pau Rabassa , Joan Carles Tatjer

We formulate and study analytically and computationally two families of piecewise linear degree one circle maps. These families offer the rare advantage of being non-trivial but essentially solvable models for the phenomenon of mode-locking…

chao-dyn · Physics 2009-10-28 David K. Campbell , Roza Galeeva , Charles Tresser , David J. Uherka

In this paper, we introduce a novel concept for learning of the parameters in a neural network. Our idea is grounded on modeling a learning problem that addresses a trade-off between (i) satisfying local objectives at each node and (ii)…

Machine Learning · Computer Science 2019-02-04 Dimche Kostadinov , Behrooz Razdehi , Slava Voloshynovskiy

Networks with long-range connections obeying a distance-dependent power law of sufficiently small exponent display superdiffusion, L\'evy flights and robustness properties very different from the scale-free networks. It has been proposed…

Adaptation and Self-Organizing Systems · Physics 2024-11-15 R. Vilela Mendes , Tanya Araújo

We show that the full features of the dynamics towards the Feigenbaum attractor, present in all low-dimensional maps with a unimodal leading component, form a hierarchical construction with modular organization that leads to a clear-cut…

Chaotic Dynamics · Physics 2015-06-12 Alberto Robledo

We study families of open chaotic maps that classically share the same asymptotic properties -- forward and backwards trapped sets, repeller dimensions, escape rate -- but differ in their short time behavior. When these maps are quantized…

Quantum Physics · Physics 2013-01-31 Leonardo Ermann , Gabriel G. Carlo , Juan M. Pedrosa , Marcos Saraceno

Deep functional map frameworks are widely employed for 3D shape matching. However, most existing deep functional map methods cannot adaptively capture important frequency information for functional map estimation in specific matching…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Feifan Luo , Qinsong Li , Ling Hu , Haibo Wang , Xinru Liu , Shengjun Liu , Hongyang Chen

We identify two broad types of noninvertibilities in quantum dynamical maps, one necessarily associated with CP indivisibility and one not so. We study the production of (non-)Markovian, invertible maps by the process of mixing…

Quantum Physics · Physics 2023-10-17 Vinayak Jagadish , R. Srikanth , Francesco Petruccione

In a recent paper by Cabrera et al (Chaos, Solitons and Fractals 2021 146 110876), a linearization of DRM differences equation, (Delayed Regulation Model), has been proposed as a scheme to explain transfer of energy through different scales…

Statistical Mechanics · Physics 2023-09-07 Juan S. Medina-Alvarez

This paper defines a linear representation for nonlinear maps $F:\mathbb{F}^n\rightarrow\mathbb{F}^n$ where $\mathbb{F}$ is a finite field, in terms of matrices over $\mathbb{F}$. This linear representation of the map $F$ associates a…

Symbolic Computation · Computer Science 2024-04-04 Ramachandran Anantharaman , Virendra Sule

Results and tools on discrete interaction networks are often concerned with Boolean variables, whereas considering more than two levels is sometimes useful. Multivalued networks can be converted to partial Boolean maps, in a way that…

Discrete Mathematics · Computer Science 2018-12-11 Elisa Tonello

We adapt previous research on category theory and topological unsupervised learning to develop a functorial perspective on manifold learning, also known as nonlinear dimensionality reduction. We first characterize manifold learning…

Machine Learning · Computer Science 2022-11-04 Dan Shiebler

An autoregressive model with a power-law type memory kernel is studied as a stochastic process that exhibits a self-affine-fractal-like behavior for a small time scale. We find numerically that the root-mean-square displacement for the time…

Statistical Mechanics · Physics 2015-10-28 Hidetsugu Sakaguchi , Haruo Honjo

The intrinsic nature of a problem usually suggests a first suitable method to deal with it. Unfortunately, the apparent ease of application of these initial approaches may make their possible flaws seem to be inherent to the problem and…

Classical Analysis and ODEs · Mathematics 2022-02-17 Victoriano Carmona , Fernando Fernández-Sánchez

Neutral particles can be guided and focussed using electric field gradients that focus in one transverse direction and defocus in the other, alternating between the two directions. Such a guide is suitable for transporting particles that…

Atomic Physics · Physics 2008-12-22 M. R. Tarbutt , E. A. Hinds

Representation of data on mixed variables, numerical and categorical types to get suitable feature map is a challenging task as important information lies in a complex non-linear manifold. The feature transformation should be able to…

Machine Learning · Computer Science 2020-09-22 Saswata Sahoo , Souradip Chakraborty

Abstrct: In this note, by considering fractionally linear functions over a finite field and consequently developing an abstract sequence, we study some of its properties.

Discrete Mathematics · Computer Science 2007-05-23 V. M. Siddlenikov , R. N. Mohan , Moon Ho Lee

If a point particle moves chaotically through a periodic array of scatterers the associated transport coefficients are typically irregular functions under variation of control parameters. For a piecewise linear two-parameter map we analyze…

Chaotic Dynamics · Physics 2009-11-10 R. Klages , T. Klauss
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