Filter Results

21989 results

- Cross-
**frequency**coupling... Steps applied to compute both CFC and CFD. (A) High**frequency**power at**frequency**v is estimated from the original signal by applying a sliding Hanning tapered time window followed by a Fourier transformation (red line). After that, both the original signal and the power envelope of the high**frequency**signal are divided into segments. Within each segment, the original signal and the power envelope of the high**frequency**signal are Fourier-transformed and cross-spectra between them are computed. (B) CFC and CFD quantification. CFC is quantified by coherence and CFD is calculated from the PSI between the phase of slow**oscillation**fi and power of fast**oscillation**vj. The red segment indicates the**frequency**range over which the PSI is calculated. The PSI is calculated for the bandwidth β. ... Statistical assessment of the CFC and CFD when controlling for multiple comparisons over**frequencies**. (A) Observed CFC/D and clustering threshold. All observed CFC/D values were pooled together (i.e. all**frequency**by**frequency**bins) and the threshold is set at the 99.5th percentile of the resulting distribution (right panel). Contiguous CFC/D values exceeding the threshold formed a cluster (left panel). The summed CFC/D values from a given cluster were considered the cluster score. (B) Circular shifted CFC/D and the cluster reference distribution. Random number of the Fourier-transferred phase segment sequences was circular shifted with respect to the amplitude envelope segments and the CFC/D values were recomputed 1000 times. For each randomization, the CFC/D contiguous values exceeding the threshold were used to form reference clusters (e.g., cluster1, cluster2, and so on in the left panel) and the respective cluster scores were calculated. The resulting 1000 maximum cluster scores formed the cluster-level reference distribution. For the observed cluster score, the p value was determined by considering the fraction of cluster scores in the reference distribution exceeding the observed cluster score (right panel). ... Neuronal**oscillations**... Phase spectra between low**frequency**signal and high**frequency**envelope. The red curves represent the envelope of high**frequency**signals. Fig. 1 is adapted from Schoffelen et al. (2005). Left panel: The low**frequency**signal is leading the high**frequency**envelope by 10ms. This constant lead translates into a phase-lead that linearly increases with**frequency**(e.g., 0.25rad for 4Hz, 0.50rad for 8Hz and 0.75rad for 12Hz). Right panel: The low**frequency**signal is lagging the high**frequency**envelope by 10ms. This constant lag translates into a phase-lag that linearly decreases with**frequency**(e.g., −0.25rad for 4Hz, −0.50rad for 8Hz and −0.75rad for 12Hz). ... Cross-**frequency**directionalityData Types:- Image

- The period of
**oscillation**T0 in a QR as a function of the transverse and longitudinal effective confinement lengths of the QR lp and lv. ... The period of**oscillation**T0 in a QR as a function of the electron–phonon coupling strength α and the Coulomb bound potential β. ...**Qubit**... The period of**oscillation**T0 in a QR as a function of the ellipsoid aspect ratio e′ and the electron–phonon coupling strength α.Data Types:- Image

- Adaptive
**frequency****oscillator**... The left plot of this figure represents the evolution of ω(t) when the adaptive Hopf**oscillator**is coupled to the z variable of the Lorenz attractor. The right plot represents the z variable of the Lorenz attractor. We clearly see that the adaptive Hopf**oscillators**can correctly learn the pseudo-**frequency**of the Lorenz attractor. See the text for more details. ... Plots of the**frequency**of the**oscillations**of the Van der Pol**oscillator**according to ω. Here α=50. There are two plots, for the dotted line the**oscillator**is not coupled and for the plain line the**oscillator**is coupled to F=sin30t. The strength of coupling is ϵ=2. We clearly see basins of phase-locking, the main one for**frequency**of**oscillations**30. The other major basins appear each 30n (dotted horizontal lines). We also notice small entrainment basins for some**frequencies**of the form 30pq. For a more detailed discussion of these results refer to the text. ... We show the adaptation of the Van der Pol**oscillator**to the**frequencies**of various input signals: (a) a simple sinusoidal input (F=sin(40t)), (b) a sinusoidal input with uniformly distributed noise (F=sin(40t)+uniform noise in [−0.5,0.5]), (c) a square input (F=square(40t)) and (d) a sawtooth input (F=sawtooth(40t)). For each experiment, we set ϵ=0.7 and α=100 and we show three plots. The right one shows the evolution of ω(t). The upper left graph is a plot of the**oscillations**, x, of the system, at the beginning of the learning. The lower graph shows the**oscillations**at the end of learning. In both graphs, we also plotted the input signal (dashed). In each experiment, ω converges to ω≃49.4, which corresponds to**oscillations**with a**frequency**of 40 rad s−1 like the input and thus the**oscillator**correctly adapts its**frequency**to the**frequency**of the input. ...**Frequency**spectra of the Van der Pol**oscillator**, both plotted with ω=10. The left figure is an**oscillator**with α=10 and on the right the nonlinearity is higher, α=50. On the y-axis we plotted the square root of the power intensity, in order to be able to see smaller**frequency**components. ... This figure shows the convergence of ω for several initial**frequencies**. The Van der Pol**oscillator**is perturbed by F=sin(30t), with coupling ϵ=0.7, α=50. We clearly see that the convergence directly depends on the initial conditions and as expected the different kinds of convergence correspond to the several entrainment basins of Fig. 7.Data Types:- Image
- Tabular Data

- Traveling wave resonator with two ports incorporated into interferometric
**frequency**discriminator for**oscillator**stabilisation. ... Modified Galani**oscillator**stabilisation technique utilising travelling wave resonator with standing wave ratio. ...**Frequency**Standards and Metrology Group, School of Physics, University of Western Australia, 35 Stirling Hwy, Crawley 6009, AustraliaData Types:- Image

- The phase of the
**oscillator**after action of a linearly-chirped pulsed force as a function of the chirp strength. In this case Ω0=4, σ=5. ... The amplitude of a harmonic**oscillator**after the action of a pulsed force with a Gaussian envelope and a linear chirp in dependence on the chirp strength, ΔΩ. In this case Ω0=5 and σ=5, 10, and 20; A=1 in all figures. ... The amplitude of the**oscillator**after the action of a force with an asymmetrical Gaussian envelope, σ1=5, Ω0=5, σ2=10 and 20. ... The amplitude of the**oscillator**vs. ΔΩ in the case of a periodical chirp in the force. The parameters of the force are: Ω0=5, σ=20, b=4. ... Classical**oscillator**...**Frequency**chirpData Types:- Image

- Dominant
**frequencies**of 10mm nozzle. ... Condensation regime map by Cho et al. [1] (C–chugging, TC—transitional region from chugging to CO, CO—condensation**oscillation**, SC—stable condensation, BCO—bubble condensation**oscillation**, IOC—interfacial**oscillation**condensation). ... Condensation**oscillation**...**Frequencies**at different test conditions—250kgm−2s−1. ...**Frequency**... Prediction accuracy of simultaneous equations for**oscillation****frequency**. ...**Frequencies**at different test conditions—300kgm−2s−1.Data Types:- Image
- Tabular Data

- Driven
**qubit**Data Types:- Image

**Frequency**modulation...**Frequency**modulated Ca2+**oscillations**. (A) A computer generated (in silico)**oscillating**wave with the parameters: period (T),**frequency**(f), full duration half maximum (FDHM), and duty cycle is depicted. (B)**Oscillating**wave**frequency**modulated by agonist concentration. (C)**Oscillating**wave**frequency**modulated by the different agonists X, Y, and Z. Three single cell Ca2+ recordings of a Fluo-4/AM-loaded neuroblastoma cell (D), HeLa cell (E), and cardiac cell (F) with the parameters T, f, FDHM, and duty cycle stated. Scale bars are 100s. ...**Frequency**decoders and host cells. Illustration showing the**frequencies**and periods that modulate the different**frequency**decoders and host cells. ...**Frequency**decodingData Types:- Image

- PES of the
**qubit**system (a) and total dipole surface (b). For both surfaces: −52.8 pm⩽rA1⩽+52.8pm and −37.4pm⩽rE⩽+37.4pm. ... Normal modes included in the quantum dynamical calculation. (a) Coordinates of the**qubit**modes, (b) coordinates of the non-**qubit**modes. ... Spectral analysis of the NOT (top) and CNOT (bottom) gate. The solid lines correspond to the spectra of the optimized pulses, the dashed lines to the spectra of the sub pulses. The vertical lines indicate the relevant**qubit**basis transition**frequencies**for the quantum gates. ... spectroscopical data of the**qubit**vibrational modes E and A1 and the non-**qubit**modes, the δ-deformation mode (E) and the dissociative mode (A1)Data Types:- Image
- Tabular Data

- We consider the interaction between a single cavity mode and N≫1 identical
**qubits**, assuming that any system parameter can be rapidly modulated in situ by external bias. It is shown that, for the**qubits**initially in the ground states, three photons can be coherently annihilated in the dispersive regime for harmonic modulation with**frequency**3ω0−Ω0, where ω0 (Ω0) is the bare cavity (**qubit**)**frequency**. This phenomenon can be called “Anti-dynamical Casimir effect”, since a pair of excitations is destroyed without dissipation due to the external modulation. For the initial vacuum cavity state, three**qubit**excitations can also be annihilated for the modulation**frequency**3Ω0−ω0.Data Types:- Image

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