225 research outputs found
Operator algebra quantum homogeneous spaces of universal gauge groups
In this paper, we quantize universal gauge groups such as SU(\infty), as well
as their homogeneous spaces, in the sigma-C*-algebra setting. More precisely,
we propose concise definitions of sigma-C*-quantum groups and sigma-C*-quantum
homogeneous spaces and explain these concepts here. At the same time, we put
these definitions in the mathematical context of countably compactly generated
spaces as well as C*-compact quantum groups and homogeneous spaces. We also
study the representable K-theory of these spaces and compute it for the quantum
homogeneous spaces associated to the universal gauge group SU(\infty).Comment: 14 pages. Merged with [arXiv:1011.1073
Synthesizing attractors of Hindmarsh-Rose neuronal systems
In this paper a periodic parameter switching scheme is applied to the
Hindmarsh-Rose neuronal system to synthesize certain attractors. Results show
numerically, via computer graphic simulations, that the obtained synthesized
attractor belongs to the class of all admissible attractors for the
Hindmarsh-Rose neuronal system and matches the averaged attractor obtained with
the control parameter replaced with the averaged switched parameter values.
This feature allows us to imagine that living beings are able to maintain vital
behavior while the control parameter switches so that their dynamical behavior
is suitable for the given environment.Comment: published in Nonlinear Dynamic
Dynamics of FitzHugh-Nagumo excitable systems with delayed coupling
Small lattices of nearest neighbor coupled excitable FitzHugh-Nagumo
systems, with time-delayed coupling are studied, and compared with systems of
FitzHugh-Nagumo oscillators with the same delayed coupling. Bifurcations of
equilibria in N=2 case are studied analytically, and it is then numerically
confirmed that the same bifurcations are relevant for the dynamics in the case
. Bifurcations found include inverse and direct Hopf and fold limit cycle
bifurcations. Typical dynamics for different small time-lags and coupling
intensities could be excitable with a single globally stable equilibrium,
asymptotic oscillatory with symmetric limit cycle, bi-stable with stable
equilibrium and a symmetric limit cycle, and again coherent oscillatory but
non-symmetric and phase-shifted. For an intermediate range of time-lags inverse
sub-critical Hopf and fold limit cycle bifurcations lead to the phenomenon of
oscillator death. The phenomenon does not occur in the case of FitzHugh-Nagumo
oscillators with the same type of coupling.Comment: accepted by Phys.Rev.
To be or not to be? What molecules say about Runcina brenkoae Thompson, 1980 (Gastropoda: Heterobranchia: Runcinida)
Runcinids are poorly known minute marine slugs inhabiting intertidal and shallow subtidal rocky shores. Among the European species, Runcina brenkoae, described from the Adriatic Sea in the Mediterranean, has been described to display chromatic variability, placing in question the true identity and geographic distribution of the species. In this paper we investigate the taxonomic status of R. brenkoae based on specimens from the central and western Mediterranean Sea and the southern Iberian coastline of Portugal and Spain, following an integrative approach combining multi-locus molecular phylogenetics based on the mitochondrial markers cytochrome c oxidase subunit I and 16S rRNA and the nuclear gene histone H3, together with the study of morpho-anatomical characters investigated by scanning electron microscopy. To aid in species delimitation, the Automatic Barcode Gap Discovery and Bayesian Poisson tree process methods were employed. Our results indicate the existence of a complex of three species previously identified as R. brenkoae, namely two new species here described (R. marcosi n. sp. and R. lusitanica n. sp.) and R. brenkoae proper
Coherence Resonance and Noise-Induced Synchronization in Globally Coupled Hodgkin-Huxley Neurons
The coherence resonance (CR) of globally coupled Hodgkin-Huxley neurons is
studied. When the neurons are set in the subthreshold regime near the firing
threshold, the additive noise induces limit cycles. The coherence of the system
is optimized by the noise. A bell-shaped curve is found for the peak height of
power spectra of the spike train, being significantly different from a
monotonic behavior for the single neuron. The coupling of the network can
enhance CR in two different ways. In particular, when the coupling is strong
enough, the synchronization of the system is induced and optimized by the
noise. This synchronization leads to a high and wide plateau in the local
measure of coherence curve. The local-noise-induced limit cycle can evolve to a
refined spatiotemporal order through the dynamical optimization among the
autonomous oscillation of an individual neuron, the coupling of the network,
and the local noise.Comment: five pages, five figure
Stochastic Resonance in Ion Channels Characterized by Information Theory
We identify a unifying measure for stochastic resonance (SR) in voltage
dependent ion channels which comprises periodic (conventional), aperiodic and
nonstationary SR. Within a simplest setting, the gating dynamics is governed by
two-state conductance fluctuations, which switch at random time points between
two values. The corresponding continuous time point process is analyzed by
virtue of information theory. In pursuing this goal we evaluate for our
dynamics the tau-information, the mutual information and the rate of
information gain. As a main result we find an analytical formula for the rate
of information gain that solely involves the probability of the two channel
states and their noise averaged rates. For small voltage signals it simplifies
to a handy expression. Our findings are applied to study SR in a potassium
channel. We find that SR occurs only when the closed state is predominantly
dwelled. Upon increasing the probability for the open channel state the
application of an extra dose of noise monotonically deteriorates the rate of
information gain, i.e., no SR behavior occurs.Comment: 10 pages, 2 figures, to appear in Phys. Rev.
Synchronisation in networks of delay-coupled type-I excitable systems
We use a generic model for type-I excitability (known as the SNIPER or SNIC
model) to describe the local dynamics of nodes within a network in the presence
of non-zero coupling delays. Utilising the method of the Master Stability
Function, we investigate the stability of the zero-lag synchronised dynamics of
the network nodes and its dependence on the two coupling parameters, namely the
coupling strength and delay time. Unlike in the FitzHugh-Nagumo model (a model
for type-II excitability), there are parameter ranges where the stability of
synchronisation depends on the coupling strength and delay time. One important
implication of these results is that there exist complex networks for which the
adding of inhibitory links in a small-world fashion may not only lead to a loss
of stable synchronisation, but may also restabilise synchronisation or
introduce multiple transitions between synchronisation and desynchronisation.
To underline the scope of our results, we show using the Stuart-Landau model
that such multiple transitions do not only occur in excitable systems, but also
in oscillatory ones.Comment: 10 pages, 9 figure
Evolving unipolar memristor spiking neural networks
© 2015 Taylor & Francis. Neuromorphic computing – brain-like computing in hardware – typically requires myriad complimentary metal oxide semiconductor spiking neurons interconnected by a dense mesh of nanoscale plastic synapses. Memristors are frequently cited as strong synapse candidates due to their statefulness and potential for low-power implementations. To date, plentiful research has focused on the bipolar memristor synapse, which is capable of incremental weight alterations and can provide adaptive self-organisation under a Hebbian learning scheme. In this paper, we consider the unipolar memristor synapse – a device capable of non-Hebbian switching between only two states (conductive and resistive) through application of a suitable input voltage – and discuss its suitability for neuromorphic systems. A self-adaptive evolutionary process is used to autonomously find highly fit network configurations. Experimentation on two robotics tasks shows that unipolar memristor networks evolve task-solving controllers faster than both bipolar memristor networks and networks containing constant non-plastic connections whilst performing at least comparably
Linear stability analysis of retrieval state in associative memory neural networks of spiking neurons
We study associative memory neural networks of the Hodgkin-Huxley type of
spiking neurons in which multiple periodic spatio-temporal patterns of spike
timing are memorized as limit-cycle-type attractors. In encoding the
spatio-temporal patterns, we assume the spike-timing-dependent synaptic
plasticity with the asymmetric time window. Analysis for periodic solution of
retrieval state reveals that if the area of the negative part of the time
window is equivalent to the positive part, then crosstalk among encoded
patterns vanishes. Phase transition due to the loss of the stability of
periodic solution is observed when we assume fast alpha-function for direct
interaction among neurons. In order to evaluate the critical point of this
phase transition, we employ Floquet theory in which the stability problem of
the infinite number of spiking neurons interacting with alpha-function is
reduced into the eigenvalue problem with the finite size of matrix. Numerical
integration of the single-body dynamics yields the explicit value of the
matrix, which enables us to determine the critical point of the phase
transition with a high degree of precision.Comment: Accepted for publication in Phys. Rev.
- …