395 research outputs found

    Strong and weak semiclassical limits for some rough Hamiltonians

    Full text link
    We present several results concerning the semiclassical limit of the time dependent Schr\"odinger equation with potentials whose regularity doesn't guarantee the uniqueness of the underlying classical flow. Different topologies for the limit are considered and the situation where two bicharateristics can be obtained out of the same initial point is emphasized

    Empirical Mode Decomposition as a Filter Bank

    Full text link

    Exact equations for smoothed Wigner transforms and homogenization of wave propagation

    Get PDF
    The Wigner Transform (WT) has been extensively used in the formulation of phase-space models for a variety of wave propagation problems including high-frequency limits, nonlinear and random waves. It is well known that the WT features counterintuitive 'interference terms', which often make computation impractical. In this connection, we propose the use of the smoothed Wigner Transform (SWT), and derive new, exact equations for it, covering a broad class of wave propagation problems. Equations for spectrograms are included as a special case. The 'taming' of the interference terms by the SWT is illustrated, and an asymptotic model for the Schroedinger equation is constructed and numerically verified.Comment: 16 pages, 8 figure

    Regional coherence evaluation in mild cognitive impairment and Alzheimer's disease based on adaptively extracted magnetoencephalogram rhythms

    Get PDF
    This study assesses the connectivity alterations caused by Alzheimer's disease (AD) and mild cognitive impairment (MCI) in magnetoencephalogram (MEG) background activity. Moreover, a novel methodology to adaptively extract brain rhythms from the MEG is introduced. This methodology relies on the ability of empirical mode decomposition to isolate local signal oscillations and constrained blind source separation to extract the activity that jointly represents a subset of channels. Inter-regional MEG connectivity was analysed for 36 AD, 18 MCI and 26 control subjects in δ, θ, α and β bands over left and right central, anterior, lateral and posterior regions with magnitude squared coherence—c(f). For the sake of comparison, c(f) was calculated from the original MEG channels and from the adaptively extracted rhythms. The results indicated that AD and MCI cause slight alterations in the MEG connectivity. Computed from the extracted rhythms, c(f) distinguished AD and MCI subjects from controls with 69.4% and 77.3% accuracies, respectively, in a full leave-one-out cross-validation evaluation. These values were higher than those obtained without the proposed extraction methodology

    Spectral Analysis of Multi-dimensional Self-similar Markov Processes

    Full text link
    In this paper we consider a discrete scale invariant (DSI) process {X(t),tR+}\{X(t), t\in {\bf R^+}\} with scale l>1l>1. We consider to have some fix number of observations in every scale, say TT, and to get our samples at discrete points αk,kW\alpha^k, k\in {\bf W} where α\alpha is obtained by the equality l=αTl=\alpha^T and W={0,1,...}{\bf W}=\{0, 1,...\}. So we provide a discrete time scale invariant (DT-SI) process X()X(\cdot) with parameter space {αk,kW}\{\alpha^k, k\in {\bf W}\}. We find the spectral representation of the covariance function of such DT-SI process. By providing harmonic like representation of multi-dimensional self-similar processes, spectral density function of them are presented. We assume that the process {X(t),tR+}\{X(t), t\in {\bf R^+}\} is also Markov in the wide sense and provide a discrete time scale invariant Markov (DT-SIM) process with the above scheme of sampling. We present an example of DT-SIM process, simple Brownian motion, by the above sampling scheme and verify our results. Finally we find the spectral density matrix of such DT-SIM process and show that its associated TT-dimensional self-similar Markov process is fully specified by {RjH(1),RjH(0),j=0,1,...,T1}\{R_{j}^H(1),R_{j}^H(0),j=0, 1,..., T-1\} where RjH(τ)R_j^H(\tau) is the covariance function of jjth and (j+τ)(j+\tau)th observations of the process.Comment: 16 page

    The Hurst Exponent of Fermi GRBs

    Full text link
    Using a wavelet decomposition technique, we have extracted the Hurst exponent for a sample of 46 long and 22 short Gamma-ray bursts (GRBs) detected by the Gamma-ray Burst Monitor (GBM) aboard the Fermi satellite. This exponent is a scaling parameter that provides a measure of long-range behavior in a time series. The mean Hurst exponent for the short GRBs is significantly smaller than that for the long GRBs. The separation may serve as an unbiased criterion for distinguishing short and long GRBs.Comment: Accepted for publication in Monthly Notices of the Royal Astronomical Societ

    Time-frequency detection of Gravitational Waves

    Get PDF
    We present a time-frequency method to detect gravitational wave signals in interferometric data. This robust method can detect signals from poorly modeled and unmodeled sources. We evaluate the method on simulated data containing noise and signal components. The noise component approximates initial LIGO interferometer noise. The signal components have the time and frequency characteristics postulated by Flanagan and Hughes for binary black hole coalescence. The signals correspond to binaries with total masses between 45M45 M_\odot to 70M70 M_\odot and with (optimal filter) signal-to-noise ratios of 7 to 12. The method is implementable in real time, and achieves a coincident false alarm rate for two detectors \approx 1 per 475 years. At this false alarm rate, the single detector false dismissal rate for our signal model is as low as 5.3% at an SNR of 10. We expect to obtain similar or better detection rates with this method for any signal of similar power that satisfies certain adiabaticity criteria. Because optimal filtering requires knowledge of the signal waveform to high precision, we argue that this method is likely to detect signals that are undetectable by optimal filtering, which is at present the best developed detection method for transient sources of gravitational waves.Comment: 24 pages, 5 figures, uses REVTE

    On the origin of intermittency in wave turbulence

    Get PDF
    Using standard signal processing tools, we experimentally report that intermittency of wave turbulence on the surface of a fluid occurs even when two typical large-scale coherent structures (gravity wave breakings and bursts of capillary waves on steep gravity waves) are not taken into account. We also show that intermittency depends on the power injected into the waves. The dependence of the power-law exponent of the gravity-wave spectrum on the forcing amplitude cannot be also ascribed to these coherent structures. Statistics of these both events are studied.Comment: To be published in EP

    Frequency decoding of periodically timed action potentials through distinct activity patterns in a random neural network

    Full text link
    Frequency discrimination is a fundamental task of the auditory system. The mammalian inner ear, or cochlea, provides a place code in which different frequencies are detected at different spatial locations. However, a temporal code based on spike timing is also available: action potentials evoked in an auditory-nerve fiber by a low-frequency tone occur at a preferred phase of the stimulus-they exhibit phase locking-and thus provide temporal information about the tone's frequency. In an accompanying psychoacoustic study, and in agreement with previous experiments, we show that humans employ this temporal information for discrimination of low frequencies. How might such temporal information be read out in the brain? Here we demonstrate that recurrent random neural networks in which connections between neurons introduce characteristic time delays, and in which neurons require temporally coinciding inputs for spike initiation, can perform sharp frequency discrimination when stimulated with phase-locked inputs. Although the frequency resolution achieved by such networks is limited by the noise in phase locking, the resolution for realistic values reaches the tiny frequency difference of 0.2% that has been measured in humans.Comment: 16 pages, 5 figures, and supplementary informatio
    corecore