Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Nonlinear Dynamics”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,441 records · Page 80Linked to original sources
PubMed2000

Denoising human speech signals using chaoslike features.

A local projective noise reduction scheme, originally developed for low-dimensional stationary deterministic chaotic signals, is successfully applied to human speech. This is possible by exploiting properties of the speech signal which resemble structure exhibited by deterministic dynamical systems. In high-dimensional embedding spaces, the strong inherent nonstationarity is resolved as a sequence of many different dynamical regimes of moderate complexity.

Humans↗
PubMed2000

A simple model for complex dynamical transitions in epidemics.

Dramatic changes in patterns of epidemics have been observed throughout this century. For childhood infectious diseases such as measles, the major transitions are between regular cycles and irregular, possibly chaotic epidemics, and from regionally synchronized oscillations to complex, spatially incoherent epidemics. A simple model can explain both kinds of transitions as the consequences of changes in birth and vaccination rates. Measles is a natural ecological system that exhibits different dynamical transitions at different times and places, yet all of these transitions can be predicted as bifurcations of a single nonlinear model.

Baltimore↗
PubMed1996

The importance of noise for segmentation and binding in dynamical neural systems.

Segmentation and binding are cognitive operations that underlie the process of perception. They can be understood as taking place in the temporal domain. In models of nonlinear oscillatory neurons and neuronal cell assemblies, we represent binding by phase locking of assemblies in different networks, and segmentation by phase separation of assemblies in the same network, leading to waveforms of staggered oscillations. Both processes can be facilitated if the inputs to the system, representing simultaneously activated memories, possess noisy components. In the binding problem they serve as a tagging device, driving phase locking between assemblies that belong to different networks but carry the same inputs. In the segmentation problem they allow us to overcome an inherent limitation on segmentation that, otherwise, cannot accommodate more than a few commonly excited memories.

Artifacts↗
PubMed2006

Switching fuzzy controller design based on switching Lyapunov function for a class of nonlinear systems.

This paper presents a switching fuzzy controller design for a class of nonlinear systems. A switching fuzzy model is employed to represent the dynamics of a nonlinear system. In our previous papers, we proposed the switching fuzzy model and a switching Lyapunov function and derived stability conditions for open-loop systems. In this paper, we design a switching fuzzy controller. We firstly show that switching fuzzy controller design conditions based on the switching Lyapunov function are given in terms of bilinear matrix inequalities, which is difficult to design the controller numerically. Then, we propose a new controller design approach utilizing an augmented system. By introducing the augmented system which consists of the switching fuzzy model and a stable linear system, the controller design conditions based on the switching Lyapunov function are given in terms of linear matrix inequalities (LMIs). Therefore, we can effectively design the switching fuzzy controller via LMI-based approach. A design example illustrates the utility of this approach. Moreover, we show that the approach proposed in this paper is available in the research area of piecewise linear control.

Algorithms↗
PubMed2005

Nonlinear optical studies of heme protein dynamics: implications for proteins as hybrid states of matter.

Protein structure is fundamentally related to function. However, static structures alone are insufficient to understand how a protein works. Dynamics play an equally important role. Given that proteins are highly associated aperiodic systems, it may be expected that protein dynamics would follow glass-like dynamics. However, protein functions occur on time scales orders of magnitude faster than the time scales typically associated with glassy systems. It is becoming clear that the reaction forces driving functions do not sample entirely the large number of configurations available to a protein but are highly directed along an optimized pathway. Could there be any correlation between specific topological features in protein structures and dynamics that leads to strongly correlated atomic displacements in the dynamical response to a perturbation? This review will try to provide an answer by focusing upon recent nonlinear optical studies with the aim of directly observing functionally important protein motions over the entire dynamic range of the protein response function. The specific system chosen is photoinduced dynamics of ligand dissociation at the active site in heme proteins, with myoglobin serving as the simplest model system. The energetics and nuclear motions from the very earliest events involved in bond breaking on the femtosecond time scale all the way out to ligand escape and bimolecular rebinding on the microsecond and millisecond time scale have been mapped out. The picture that is emerging is that the system consists of strongly coupled motions from the very instant the bond breaks at the active site that cascade into low frequency collective modes specific to the protein structure. It is this coupling that imparts the ability of a protein to function on time scales more commensurate with liquids while simultaneously conserving structural integrity akin to solids.

Binding Sites↗
PubMed1999

Effects of immigration on the dynamics of simple population models.

Many simple population models exhibit the period doubling route to chaos as a single parameter, commonly the growth rate, is increased. Here we examine the effect of an immigration process on such models and explain why in the case of one-dimensional ("single-humped") maps, immigration often tends to suppress chaos and stabilise equilibrium behaviour or cyclical oscillations of long period. The conditions for which an increase of immigration "simplifies" population dynamics are examined.

Animals↗
PubMed2004

Simulated complex dynamics of glycolysis in the protozoan parasite Trypanosoma brucei.

Glycolysis in Trypanosoma brucei was modeled using a reaction transport simulator and tested for possible complex dynamics. The glycolytic model is multi-compartmentalized and accounts for the exchange of metabolites between the glycosomes, cytosol, mitochondrion and the host medium. The model is used to examine the effects of a range of culture medium concentrations of oxygen on the glycolysis of T. brucei. Our results are in good agreement with steady-state experiments. We also find that under aerobic conditions, increasing the activity of glycerol-3-phosphate dehydrogenase induces complex dynamics in the system. We report the presence of three distinct types of these dynamics. Varying the oxygen concentration in the medium can induce the transition between these dynamics.

Aerobiosis↗
PubMed1997

Self-organization in semiconductor physics.

Non-equilibrium dissipative systems from semiconductor physics have prevailed as a paradigmatic testing field for complex non-linear dynamics during the last decade. Especially, low-temperature impact ionization breakdown in extrinsic germanium crystals displays a variety of interesting nonlinear phenomena, such as spontaneous oscillations and filamentary patterns of the current flow. We report on recent experimental results concerning the interplay between spatial and temporal degrees of freedom during the onset of semiconductor breakdown. Quantitative evaluation of characteristic scaling properties supports the applicability of the model of self-organized criticality.

Biophysical Phenomena↗
PubMed1997

A nonrandom dynamic component in the synaptic noise of a central neuron.

Continuous segments of synaptic noise were recorded in vivo from teleost Mauthner cells and were studied with the methods of nonlinear analysis. As in many central neurons, this ongoing activity is dominated by consecutive inhibitory postsynaptic potentials. Recurrence plots and first or third order Poincaré maps combined with surrogate shuffling revealed nonrandom patterns consistent with the notion that synaptic noise is a continuously varying mixture of periodic and chaotic phases. Chaos was further demonstrated by the occurrence of unstable periodic orbits. The nonrandom component of the noise is reproducibly and persistently reduced when the level of background sound, a natural stimulus for networks afferent to the Mauthner cell, is briefly elevated. These data are consistent with a model involving a reciprocally connected inhibitory network, presynaptic to the Mauthner cell and its intrinsic properties. The presence of chaos in the inhibitory synaptic noise that regulates the excitability of the Mauthner cell and its sensitivity to external stimuli suggests that it modulates this neuron's function, namely to trigger a fast escape motor reaction following unexpected sensory information.

Acoustic Stimulation↗
PubMed2004

Long chaotic transients in complex networks.

We show that long chaotic transients dominate the dynamics of randomly diluted networks of pulse-coupled oscillators. This contrasts with the rapid convergence towards limit cycle attractors found in networks of globally coupled units. The lengths of the transients strongly depend on the network connectivity and vary by several orders of magnitude, with maximum transient lengths at intermediate connectivities. The dynamics of the transients exhibit a novel form of robust synchronization. An approximation to the largest Lyapunov exponent characterizing the chaotic nature of the transient dynamics is calculated analytically.

Models, Biological↗
PubMed2004

Trouble ahead: predicting antisocial trajectories with dynamic systems concepts and methods.

This paper reviews and evaluates a set of studies that utilize dynamic systems (DS) principles, and in two cases dynamic systems methods, for predicting antisocial development and other behavioral outcomes. I suggest that the emphasis of DS approaches on process and nonlinear causation is very different from the emphasis in developmental psychopathology on prediction, yet the marriage of these approaches is necessary to capture the complex interactions that give rise to problematic trajectories. The studies reviewed do indeed uncover predictive relations that would have been difficult to conceptualize or impossible to find using more traditional strategies. In discussing these studies. I suggest DS interpretations of emerging individual differences, phase-specific change, sleeper effects, mediating variables, and behavioral rigidity versus malleability, in the context of developmental prediction. I also discuss the advantages of moving from DS concepts to DS methods in clinical-developmental research.

Conduct Disorder↗
PubMed2004

Global asymptotic stability of a tracking sectorial fuzzy controller for robot manipulators.

This paper shows that fuzzy control systems satisfying sectorial properties are effective for motion tracking control of robot manipulators. We propose a controller whose structure is composed by a sectorial fuzzy controller plus a full nonlinear robot dynamics compensation, in such a way that this structure leads to a very simple closed-loop system represented by an autonomous nonlinear differential equation. We demonstrate via Lyapunov theory, that the closed-loop system is globally asymptotically stable. Experimental results show the feasibility of the proposed controller.

Journal Article↗