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Статті в журналах з теми "Phase-frequency response"

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Автор: Grafiati

Опубліковано: 30 травня 2022

Оновлено: 31 травня 2022

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1

Isaev, Alexander E., and Bulat I. Khatamtaev. "Determination of the hydrophone phase-frequency response by its amplitude-frequency response." Izmeritel`naya Tekhnika, no. 7 (2021): 48–53. http://dx.doi.org/10.32446/0368-1025it.2021-7-48-53.

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Анотація:

One of the tasks of the COOMET 786/RU/19 pilot comparisons is to check the correctness of the hydrophone model proposed in VNIIFTRI, consisting of an advance line and a minimum-phase part, including the effect of sound diffraction and resonance properties of the active element. This model makes it possible to use the Hilbert transform to obtain the phase-frequency response from the amplitude-frequency response as well as for inverse operation. The results of measuring experiments performed using facilities of the State Primary Standard GET 55-2017 are presented. For many practical tasks, it is not necessary to obtain the phase-frequency response for an acoustic center of the receiver. It is enough to determine the shape of the phase-frequency response using much less laborious methods. The question of which of the characteristics is expedient to determine during calibration - for an acoustic center, or for a point on the surface of an active element, deserves a discussion among specialists performing acoustic measurements.

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2

Isaev, A. E., and B. I. Khatamtaev. "Determination of the Hydrophone Phase-Frequency Response by its Amplitude-Frequency Response." Measurement Techniques 64, no. 7 (October 2021): 580–85. http://dx.doi.org/10.1007/s11018-021-01974-6.

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3

Polzin, Jason A., Richard Frayne, Thomas M. Grist, and Charles A. Mistretta. "Frequency response of multi-phase segmentedk-space phase-contrast." Magnetic Resonance in Medicine 35, no. 5 (May 1996): 755–62. http://dx.doi.org/10.1002/mrm.1910350517.

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4

Ganguly, Vasishta, and Tony L. Schmitz. "Phase correction for frequency response function measurements." Precision Engineering 38, no. 2 (April 2014): 409–13. http://dx.doi.org/10.1016/j.precisioneng.2013.12.007.

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5

Sato, Takuso, and Suksang Chang. "Frequency response of a micro-particle phase conjugator." Applied Optics 24, no. 17 (September 1, 1985): 2744. http://dx.doi.org/10.1364/ao.24.002744.

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6

Sarkar, B. C., M. Nandi, A. Hati, and S. Sarkar. "Noise response of tri-state phase frequency detector." Electronics Letters 33, no. 9 (1997): 744. http://dx.doi.org/10.1049/el:19970532.

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7

Van Dyke, Katlyn B., Rachel Lieberman, Alessandro Presacco, and Samira Anderson. "Development of Phase Locking and Frequency Representation in the Infant Frequency-Following Response." Journal of Speech, Language, and Hearing Research 60, no. 9 (September 18, 2017): 2740–51. http://dx.doi.org/10.1044/2017_jslhr-h-16-0263.

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Purpose This study investigates the development of phase locking and frequency representation in infants using the frequency-following response to consonant–vowel syllables. Method The frequency-following response was recorded in 56 infants and 15 young adults to 2 speech syllables (/ba/ and /ga/), which were presented in randomized order to the right ear. Signal-to-noise ratio and F sp analyses were used to verify that individual responses were present above the noise floor. Thirty-six and 39 infants met these criteria for the /ba/ or /ga/ syllables, respectively, and 31 infants met the criteria for both syllables. Data were analyzed to obtain measures of phase-locking strength and spectral magnitudes. Results Phase-locking strength to the fine structure in the consonant–vowel transition was higher in young adults than in infants, but phase locking was equivalent at the fundamental frequency between infants and adults. However, frequency representation of the fundamental frequency was higher in older infants than in either the younger infants or adults. Conclusion Although spectral amplitudes changed during the first year of life, no changes were found with respect to phase locking to the stimulus envelope. These findings demonstrate the feasibility of obtaining these measures of phase locking and fundamental pitch strength in infants as young as 2 months of age.

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8

Grzegorczyk, D. S., and G. Carta. "Frequency response of liquid-phase adsorption on polymeric adsorbents." Chemical Engineering Science 52, no. 10 (May 1997): 1589–608. http://dx.doi.org/10.1016/s0009-2509(96)00513-1.

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9

Yang, Changxi, Katuo Seta, and Yong Zhu. "Spatial-frequency response of photorefractive phase conjugators with Ce:BaTiO_3." Applied Optics 37, no. 2 (January 10, 1998): 352. http://dx.doi.org/10.1364/ao.37.000352.

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10

Unstead, P. A., and I. M. MacLeod. "Synthesis of continuous-time minimum-phase frequency response specifications." International Journal of Control 74, no. 6 (January 2001): 571–85. http://dx.doi.org/10.1080/00207170010017833.

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11

So, Won, Fan-Yin Cheng, and Craig A. Champlin. "Effects of interaural phase on the frequency following response." Journal of the Acoustical Society of America 146, no. 4 (October 2019): 2832. http://dx.doi.org/10.1121/1.5136811.

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12

Fraser, Charles D., Ken M. Brady, Christopher J. Rhee, R. Blaine Easley, Kathleen Kibler, Peter Smielewski, Marek Czosnyka, David W. Kaczka, Dean B. Andropoulos, and Craig Rusin. "The frequency response of cerebral autoregulation." Journal of Applied Physiology 115, no. 1 (July 1, 2013): 52–56. http://dx.doi.org/10.1152/japplphysiol.00068.2013.

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The frequency-response of pressure autoregulation is not well delineated; therefore, the optimal frequency of arterial blood pressure (ABP) modulation for measuring autoregulation is unknown. We hypothesized that cerebrovascular autoregulation is band-limited and delineated by a cutoff frequency for which ABP variations induce cerebrovascular reactivity. Neonatal swine ( n = 8) were anesthetized using constant minute ventilation while positive end-expiratory pressure (PEEP) was modulated between 6 and 0.75 cycles/min (min−1). The animals were hemorrhaged until ABP was below the lower limit of autoregulation (LLA), and PEEP modulations were repeated. Vascular reactivity was quantified at each frequency according to the phase lag between ABP and intracranial pressure (ICP) above and below the LLA. Phase differences between ABP and ICP were small for frequencies of >2 min−1, with no ability to differentiate cerebrovascular reactivity between ABPs above or below the LLA. For frequencies of <2 min−1, ABP and intracranial pressure (ICP) showed phase shift when measured above LLA and no phase shift when measured below LLA [above vs. below LLA at 1 min−1: 156° (139–174°) vs. 30° (22–50°); P < 0.001 by two-way ANOVA for both frequency and state of autoregulation]. Data taken above LLA fit a Butterworth high-pass filter model with a cutoff frequency at 1.8 min−1 (95% confidence interval: 1.5–2.2). Cerebrovascular reactivity occurs for sustained ABP changes lasting 30 s or longer. The ability to distinguish intact and impaired autoregulation was maximized by a 60-s wave (1 min−1), which was 100% sensitive and 100% specific in this model.

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13

Mitchell, Paul, and Laurel H. Carney. "Comparing frequency-chirp sensitivity in the inferior colliculus to basic response properties using novel stimuli." Journal of the Acoustical Society of America 151, no. 4 (April 2022): A123. http://dx.doi.org/10.1121/10.0010850.

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Most neurons in the central nucleus of the inferior colliculus (ICC) are sensitive to the direction of phase-curvature of Schroeder-phase (SCHR) stimuli. This phase-curvature controls the direction and velocity of frequency chirps within the fundamental SCHR period. Differences in responses to different SCHR stimuli may originate from an underlying sensitivity to frequency chirp direction or velocity. However, known ICC sensitivities, such as those to frequency or envelope periodicity and duty cycle, may also contribute to the observed effect. To parse these confounding SCHR stimulus features, we designed novel frequency-chirping stimuli to isolate the influences of periodicity, duty cycle, and frequency-chirp direction or velocity on ICC neuron responses. Extracellular, single-unit recordings of chirp responses were made in awake rabbit ICC. Simultaneously, basic response properties were characterized using methods such as frequency response maps, modulation transfer functions, and spectro-temporal receptive fields. By comparing basic response properties across chirp-sensitive neurons (comprising 80% of ICC neurons), we can outline the shared characteristics among them. Our goal is to determine whether frequency-chirp sensitivity in ICC neurons is independent of other established feature sensitivities. Frequency-chirp-sensitive neurons are interesting, because they may play a unique role in encoding sounds with complex phase, including speech. [Work supported by NIDCD-R01-001641.]

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14

Fowler, Cynthia G. "Effects of Stimulus Phase on the Normal Auditory Brainstem Response." Journal of Speech, Language, and Hearing Research 35, no. 1 (February 1992): 167–74. http://dx.doi.org/10.1044/jshr.3501.167.

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The purpose of this investigation was to determine the effects of stimulus phase on the latencies and morphology of the auditory brainstem response (ABR) of normal-hearing subjects. Although click stimuli produced equivalent ABR latencies for the rarefaction and condensation phases, the subtraction of the waveforms from the two phases yielded a difference potential. Tone pip stimuli produced polarity differences that were inversely related to stimulus frequency: the higher the frequency, the smaller the ABR latency differences between responses to rarefaction and condensation stimuli, and the smaller the difference potentials. Thus, whereas the latency of click-evoked ABR is dominated by high-frequency responses with equivalent latencies regardless of stimulus phase, low-frequency responses contribute to the overall morphology of the ABR that yields the phasic difference potential. The implications of these findings are discussed with reference to subjects with high-frequency hearing losses.

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15

Victor, Jonathan D., and Keith P. Purpura. "Spatial Phase and the Temporal Structure of the Response to Gratings in V1." Journal of Neurophysiology 80, no. 2 (August 1, 1998): 554–71. http://dx.doi.org/10.1152/jn.1998.80.2.554.

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Victor, Jonathan D. and Keith P. Purpura. Spatial phase and the temporal structure of the response to gratings in V1. J. Neurophysiol. 80: 554–571, 1998. We recorded single-unit activity of 25 units in the parafoveal representation of macaque V1 to transient appearance of sinusoidal gratings. Gratings were systematically varied in spatial phase and in one or two of the following: contrast, spatial frequency, and orientation. Individual responses were compared based on spike counts, and also according to metrics sensitive to spike timing. For each metric, the extent of stimulus-dependent clustering of individual responses was assessed via the transmitted information, H. In nearly all data sets, stimulus-dependent clustering was maximal for metrics sensitive to the temporal pattern of spikes, typically with a precision of 25–50 ms. To focus on the interaction of spatial phase with other stimulus attributes, each data set was analyzed in two ways. In the “pooled phases” approach, the phase of the stimulus was ignored in the assessment of clustering, to yield an index H pooled. In the “individual phases” approach, clustering was calculated separately for each spatial phase and then averaged across spatial phases to yield an index H indiv. H pooled expresses the extent to which a spike train represents contrast, spatial frequency, or orientation in a manner which is not confounded by spatial phase (phase-independent representation), whereas H indiv expresses the extent to which a spike train represents one of these attributes, provided spatial phase is fixed (phase-dependent representation). Here, representation means that a stimulus attribute has a reproducible and systematic influence on individual responses, not a neural mechanism for decoding this influence. During the initial 100 ms of the response, contrast was represented in a phase-dependent manner by simple cells but primarily in a phase-independent manner by complex cells. As the response evolved, simple cell responses acquired phase-independent contrast information, whereas complex cells acquired phase-dependent contrast information. Simple cells represented orientation and spatial frequency in a primarily phase-dependent manner, but also they contained some phase-independent information in their initial response segment. Complex cells showed primarily phase-independent representation of orientation but primarily phase-dependent representation of spatial frequency. Joint representation of two attributes (contrast and spatial frequency, contrast and orientation, spatial frequency and orientation) was primarily phase dependent for simple cells, and primarily phase independent for complex cells. In simple and complex cells, the variability in the number of spikes elicited on each response was substantially greater than the expectations of a Poisson process. Although some of this variation could be attributed to the dependence of the response on the spatial phase of the grating, variability was still markedly greater than Poisson when the contribution of spatial phase to response variance was removed.

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16

Boland, Taco, Rik Naus, and Peter Zwamborn. "Phase response reconstruction for non‐minimum phase systems using frequency‐domain magnitude values." IET Science, Measurement & Technology 15, no. 8 (April 26, 2021): 619–31. http://dx.doi.org/10.1049/smt2.12063.

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17

Alawady, A. A., M. F. M. Yousof, N. Azis, and M. A. Talib. "Phase to phase fault detection of 3-phase induction motor using FRA technique." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 3 (September 1, 2020): 1241. http://dx.doi.org/10.11591/ijpeds.v11.i3.pp1241-1248.

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The purpose for preparing this paper is to innovate a new method to detection and diagnosis the three-phase induction motor electrical failures, especially the failures that occur in Stator winding. Stator winding breakdown largely contributes to induction motor failures. To understand internal fault in induction motors winding, four cases studies of different three-phase induction motors (TPIM) were analysed according to two conditions: normal winding condition and windings shorted between two phases. In this paper, the measurement of frequency response analysis (FRA) on the stator winding with inter-phase short is presented. Additionally, Frequency Response Analysis (FRA) interpretation technique classify and quantify the fault is also proposed. For interpretation of the FRA, a statistical indicator, which is NCEPRI algorithm is used for comparison the measured responses.

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18

Isaev, Alexander E. "Analytical representation of hydrophone complex frequency response." Izmeritel`naya Tekhnika, no. 8 (2021): 16–20. http://dx.doi.org/10.32446/0368-1025it.2021-8-16-20.

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The problem of analytical representation of hydrophone complex frequency response based on a model consisting of an advance line and a minimum-phase part, which describing the effect of sound diffraction and resonance properties of an active element, is considered. Algorithms are proposed for approximating the hydrophone complex frequency response by a fractional-rational function of the complex variable according to the data of the hydrophone amplitude-frequency and/or phasefrequency responses. Examples of the application of these algorithms for processing experimental frequency characteristics of hydrophones are given.

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19

Xia, Weicheng, Ruiqi Zheng, Bijuan Chen, Erwin Chan, Xudong Wang, Xinhuan Feng, and Bai-Ou Guan. "Ripple Suppression in Broadband Microwave Photonic Phase Shifter Frequency Response." Applied Sciences 8, no. 12 (November 30, 2018): 2433. http://dx.doi.org/10.3390/app8122433.

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This paper presents a detailed investigation on the cause of ripples in the frequency response of a microwave photonic phase shifter implemented using a 90° hybrid coupler. It was found that an unwanted radio frequency (RF) modulation sideband is generated at the modulator output due to the 90° hybrid coupler amplitude and phase imbalance. This resulted in phase shifter output RF signal amplitude variation and phase deviation. Experimental results demonstrated that incorporating an optical filter in the phase shifter structure can reduce the amplitude variation and phase deviation from 4.2 dB to 2.2 dB and from ±12° to ±3.8°, respectively, over a wide frequency range. A comparison of the loss and the dynamic range of the microwave photonic phase shifter implemented using a 90° hybrid coupler with a conventional fiber optic link is also presented.

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20

Yang, Guangyao, Xinyu Fan, Qingwen Liu, and Zuyuan He. "Frequency Response Enhancement of Direct-Detection Phase-Sensitive OTDR by Using Frequency Division Multiplexing." Journal of Lightwave Technology 36, no. 4 (February 15, 2018): 1197–203. http://dx.doi.org/10.1109/jlt.2017.2767086.

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21

Chaouche, Moustafa Sahnoune, Samir Moulahoum, and Hamza Houassine. "Low and high frequency model of three phase transformer by frequency response analysis measurement." Open Physics 16, no. 1 (April 18, 2018): 117–22. http://dx.doi.org/10.1515/phys-2018-0019.

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Abstract The behavior analysis of the transformer is usually achieved by the frequency response analysis (FRA), which is obtained by the application of a very low AC voltage in over a wide frequency range. This paper presents a low and high frequency modelling approach of a three-phase transformer. The developed model consists of a cascade of parallel RLC cells, whose parameters are identified using the frequency response analysis data measurements obtained on each transformer phase. Thus, the proposed model can simulate the frequency behavior of the transformer windings without reference to the geometries of the coils which makes it easily usable in the failure diagnosis field. Experimental results on a 300 VA laboratory transformer validate the proposed model.

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22

Xianyu, Haiqing, Sebastian Gauza, and Shin‐Tson Wu. "Sub‐millisecond response phase modulator using a low crossover frequency dual‐frequency liquid crystal." Liquid Crystals 35, no. 12 (December 1, 2008): 1409–13. http://dx.doi.org/10.1080/02678290802624399.

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23

Yang, Hongzhi, Yuan Gao, Lei Wang, Sijia Wang, Peng Qing, Yefei Mao, Ziyue Zhang, and Ju Zhou. "Frequency response measurement of electro-optic phase modulators using the time-frequency analysis method." Optics Express 29, no. 26 (December 8, 2021): 42599. http://dx.doi.org/10.1364/oe.431241.

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24

Graetzel, Chauncey F., Bradley J. Nelson, and Steven N. Fry. "Frequency response of lift control in Drosophila." Journal of The Royal Society Interface 7, no. 52 (May 12, 2010): 1603–16. http://dx.doi.org/10.1098/rsif.2010.0040.

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The flight control responses of the fruitfly represent a powerful model system to explore neuromotor control mechanisms, whose system level control properties can be suitably characterized with a frequency response analysis. We characterized the lift response dynamics of tethered flying Drosophila in presence of vertically oscillating visual patterns, whose oscillation frequency we varied between 0.1 and 13 Hz. We justified these measurements by showing that the amplitude gain and phase response is invariant to the pattern oscillation amplitude and spatial frequency within a broad dynamic range. We also showed that lift responses are largely linear and time invariant (LTI), a necessary condition for a meaningful analysis of frequency responses and a remarkable characteristic given its nonlinear constituents. The flies responded to increasing oscillation frequencies with a roughly linear decrease in response gain, which dropped to background noise levels at about 6 Hz. The phase lag decreased linearly, consistent with a constant reaction delay of 75 ms. Next, we estimated the free-flight response of the fly to generate a Bode diagram of the lift response. The limitation of lift control to frequencies below 6 Hz is explained with inertial body damping, which becomes dominant at higher frequencies. Our work provides the detailed background and techniques that allow optomotor lift responses of Drosophila to be measured with comparatively simple, affordable and commercially available techniques. The identification of an LTI, pattern velocity dependent, lift control strategy is relevant to the underlying motion computation mechanisms and serves a broader understanding of insects' flight control strategies. The relevance and potential pitfalls of applying system identification techniques in tethered preparations is discussed.

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25

Frayne, Richard, and Brian K. Rutt. "Frequency response of prospectively gated phase-contrast MR velocity measurements." Journal of Magnetic Resonance Imaging 5, no. 1 (January 1995): 65–73. http://dx.doi.org/10.1002/jmri.1880050114.

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26

Tönjes, Ralf, and Hiroshi Kori. "Phase and frequency linear response theory for hyperbolic chaotic oscillators." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 4 (April 2022): 043124. http://dx.doi.org/10.1063/5.0064519.

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We formulate a linear phase and frequency response theory for hyperbolic flows, which generalizes phase response theory for autonomous limit cycle oscillators to hyperbolic chaotic dynamics. The theory is based on a shadowing conjecture, stating the existence of a perturbed trajectory shadowing every unperturbed trajectory on the system attractor for any small enough perturbation of arbitrary duration and a corresponding unique time isomorphism, which we identify as phase such that phase shifts between the unperturbed trajectory and its perturbed shadow are well defined. The phase sensitivity function is the solution of an adjoint linear equation and can be used to estimate the average change of phase velocity to small time dependent or independent perturbations. These changes in frequency are experimentally accessible, giving a convenient way to define and measure phase response curves for chaotic oscillators. The shadowing trajectory and the phase can be constructed explicitly in the tangent space of an unperturbed trajectory using co-variant Lyapunov vectors. It can also be used to identify the limits of the regime of linear response.

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27

Kupchenko, S. S., and D. P. Hess. "Mechanical Contact Frequency Response Measurements." Journal of Tribology 122, no. 4 (June 22, 2000): 828–33. http://dx.doi.org/10.1115/1.1314601.

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This paper presents friction frequency response measurements taken from a planar steel contact subjected to controlled random broadband normal vibration. Data are included from both dry and various lubricated contact conditions under different vibration input levels and different sliding velocities. Frequency response data for dry contacts are found to have nearly steady magnitude and negligible phase lag over a relatively wide range of frequencies. This suggests a coefficient of friction, independent of frequency but dependent on levels of normal acceleration and sliding velocity, may adequately define the dry contact frequency response. The frequency response data for lubricated contacts are mixed. For example, with MoS2 grease the frequency response may adequately be defined by a constant, as with dry conditions. However, frequency response data for contacts with pure mineral oils, mineral oils with additives, and lithium grease are found to be dependent on frequency. [S0742-4787(11)00101-9]

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28

Angelaki, Dora E. "Three-Dimensional Organization of Otolith-Ocular Reflexes in Rhesus Monkeys. III. Responses to Translation." Journal of Neurophysiology 80, no. 2 (August 1, 1998): 680–95. http://dx.doi.org/10.1152/jn.1998.80.2.680.

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Angelaki, Dora E. Three-dimensional organization of otolith-ocular reflexes in rhesus monkeys. III. Responses to translation. J. Neurophysiol. 80: 680–695, 1998. The three-dimensional (3-D) properties of the translational vestibulo-ocular reflexes (translational VORs) during lateral and fore-aft oscillations in complete darkness were studied in rhesus monkeys at frequencies between 0.16 and 25 Hz. In addition, constant velocity off-vertical axis rotations extended the frequency range to 0.02 Hz. During lateral motion, horizontal responses were in phase with linear velocity in the frequency range of 2–10 Hz. At both lower and higher frequencies, phase lags were introduced. Torsional response phase changed more than 180° in the tested frequency range such that torsional eye movements, which could be regarded as compensatory to “an apparent roll tilt” at the lowest frequencies, became anticompensatory at all frequencies above ∼1 Hz. These results suggest two functionally different frequency bandwidths for the translational VORs. In the low-frequency spectrum (≪0.5 Hz), horizontal responses compensatory to translation are small and high-pass-filtered whereas torsional response sensitivity is relatively frequency independent. At higher frequencies however, both horizontal and torsional response sensitivity and phase exhibit a similar frequency dependence, suggesting a common role during head translation. During up-down motion, vertical responses were in phase with translational velocity at 3–5 Hz but phase leads progressively increased for lower frequencies (>90° at frequencies <0.2 Hz). No consistent dependence on static head orientation was observed for the vertical response components during up-down motion and the horizontal and torsional response components during lateral translation. The frequency response characteristics of the translational VORs were fitted by “periphery/brain stem” functions that related the linear acceleration input, transduced by primary otolith afferents, to the velocity signals providing the input to the velocity-to-position neural integrator and the oculomotor plant. The lowest-order, best-fit periphery/brain stem model that approximated the frequency dependence of the data consisted of a second order transfer function with two alternating poles (at 0.4 and 7.2 Hz) and zeros (at 0.035 and 3.4 Hz). In addition to clearly differentiator dynamics at low frequencies (less than ∼0.5 Hz), there was no frequency bandwidth where the periphery/brain stem function could be approximated by an integrator, as previously suggested. In this scheme, the oculomotor plant dynamics are assumed to perform the necessary high-frequency integration as required by the reflex. The detailed frequency dependence of the data could only be precisely described by higher order functions with nonminimum phase characteristics that preclude simple filtering of afferent inputs and might be suggestive of distributed spatiotemporal processing of otolith signals in the translational VORs.

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29

Jaikla, Winai, Unchittha Buakhong, Surapong Siripongdee, Fabian Khateb, Roman Sotner, Phamorn Silapan, Peerawut Suwanjan, and Amornchai Chaichana. "Single Commercially Available IC-Based Electronically Controllable Voltage-Mode First-Order Multifunction Filter with Complete Standard Functions and Low Output Impedance." Sensors 21, no. 21 (November 6, 2021): 7376. http://dx.doi.org/10.3390/s21217376.

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This paper presents the design of a voltage-mode three-input single-output multifunction first-order filter employing commercially available LT1228 IC for easy verification of the proposed circuit by laboratory measurements. The proposed filter is very simple, consisting of a single LT1228 as an active device with two resistors and one capacitor. The output voltage node is low impedance, resulting in an easy cascade-ability with other voltage-mode configurations. The proposed filter provides four filter responses: low-pass filter (LP), high-pass filter (HP), inverting all-pass filter (AP−), and non-inverting all-pass filter (AP+) in the same circuit configuration. The selection of output filter responses can be conducted without additional inverting or double gains, which is easy to be controlled by the digital method. The control of pole frequency and phase response can be conducted electronically through the bias current (IB). The matching condition during tuning the phase response with constant voltage gain is not required. Moreover, the pass-band voltage gain of the LP and HP functions can be controlled by adjusting the value of resistors without affecting the pole frequency and phase response. Additionally, the phase responses of the AP filters can be selected as both lagging or leading phase responses. The parasitic effects on the filtering performances were also analyzed and studied. The performances of the proposed filter were simulated and experimented with a ±5 V voltage supply. For the AP+ experimental result, the leading phase response for 1 kHz to 1 MHz frequency changed from 180 to 0 degrees. For the AP− experimental result, the lagging phase response for 1 kHz to 1 MHz frequency changed from 0 to −180 degrees. The design of the quadrature oscillator based on the proposed first-order filter is also included as an application example.

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30

Younes, M., and R. Sanii. "Effect of phase shifts in pressure-flow relationship on response to inspiratory resistance." Journal of Applied Physiology 67, no. 2 (August 1, 1989): 699–706. http://dx.doi.org/10.1152/jappl.1989.67.2.699.

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Inspiratory prolongation is an integral component of the response to added inspiratory resistance. To ascertain whether this response depends on the relation between inspiratory flow (V) and the pressure perturbation, we compared the responses when this relationship was made progressively less distinct by creating phase shifts between V and the resulting negative mouth pressure (Pm). This was done with an apparatus that altered Pm in proportion to V (J. Appl. Physiol. 62:2491–2499, 1987). V was passed through low-pass electronic filters of different frequency responses before serving as the command signal to the apparatus. In six normal subjects the average neural inspiratory duration (TI) response (delta TI) was sharply (P less than 0.01) reduced (0.32 +/- 0.07 to 0.12 +/- 0.07 s) when the filter's frequency response decreased from 7.5 to 3.0 Hz. The TI response was essentially flat between tube resistance (i.e., no lag, delta TI = 0.36 +/- 0.11 s) and the 7.5-Hz filter, and there was no further change in TI response with filters having a frequency response less than 3.0 Hz, with all TI responses in this range being not significant. Subjects could not consciously perceive a difference between various filter settings. We conclude that the TI response is critically influenced by the phase of the negative pressure wave relative to TI. Furthermore the TI responses are not deliberate, although consciousness is required for their elicitation.

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31

Li, Gang, Wen Qi, Zhiqiang Huang, and Zhifei Tao. "Modal characteristics and phase response of vibrator under excitation of sweep frequency." Advances in Mechanical Engineering 12, no. 11 (November 2020): 168781402097117. http://dx.doi.org/10.1177/1687814020971175.

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Анотація:

To analyze the dynamic responses of vibrator, a vibrator-ground coupling vibration model considering sweep frequency is proposed based on half-space theory, and modal characteristics and phase response of the structure are investigated. Results show that the sweep frequency has a significant effect on the dynamic responses of the vibrator. The natural frequency of the vibrator changes with sweep frequency, and the resonance may occur at 2.071 Hz and 53.12 Hz. The vibrator has two mode shapes. The first-order mode shape is that the reaction mass and the baseplate move in the same direction and the structure is dominated by the reaction mass. At the second-order resonance, the reaction mass and the baseplate move in opposite directions and the baseplate dominates the system. The phase of the vibrator also changes with the frequency and varies greatly. The phases of reaction mass acceleration, baseplate acceleration and ground force suffer abrupt changes at about 2 Hz and 50 Hz. Especially, the phase of the baseplate acceleration experiences a 180° jumping at about 50 Hz. The abrupt change/jumping frequencies of the phase are basically the same as the natural frequencies, indicating that the resonance has significant effect on the vibrator output.

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32

Zaitsev, V. G. "Application of the phase-frequency response in studies of oscillation systems." Journal of Machinery Manufacture and Reliability 39, no. 3 (June 2010): 232–37. http://dx.doi.org/10.3103/s1052618810030040.

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33

Liang, Xiaodong, Ahmed El-Kadri, John Stevens, and Rotimi Adedun. "Frequency Response Analysis for Phase-Shifting Transformers in Oil Field Facilities." IEEE Transactions on Industry Applications 50, no. 4 (July 2014): 2861–70. http://dx.doi.org/10.1109/tia.2013.2291936.

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34

Crespo, Daniel, Juan Antonio Quiroga, and Jose Antonio Gomez-Pedrero. "Design of asynchronous phase detection algorithms optimized for wide frequency response." Applied Optics 45, no. 17 (June 10, 2006): 4037. http://dx.doi.org/10.1364/ao.45.004037.

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35

Heng, Yuqing, Min Xue, Wei Chen, Shunli Han, Jiaqing Liu, and Shilong Pan. "Large-Dynamic Frequency Response Measurement for Broadband Electro-Optic Phase Modulators." IEEE Photonics Technology Letters 31, no. 4 (February 15, 2019): 291–94. http://dx.doi.org/10.1109/lpt.2019.2891890.

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36

Ye, Quanyi, Chun Yang, and Yuhua Chong. "Measuring the Frequency Response of Photodiode Using Phase-Modulated Interferometric Detection." IEEE Photonics Technology Letters 26, no. 1 (January 2014): 29–32. http://dx.doi.org/10.1109/lpt.2013.2280767.

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37

Lian, Y., and Y. C. Lim. "Zeros of linear phase FIR filter with piecewise constant frequency response." Electronics Letters 28, no. 2 (1992): 203. http://dx.doi.org/10.1049/el:19920126.

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38

Nazarathy, M., D. Dolfi, and R. Jungerman. "Spread spectrum frequency response of coded phase reversal traveling wave modulators." Journal of Lightwave Technology 5, no. 10 (1987): 1433–43. http://dx.doi.org/10.1109/jlt.1987.1075429.

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39

Isler, Joseph R., Philip G. Grieve, D. Czernochowski, Raymond I. Stark, and David Friedman. "Cross-frequency phase coupling of brain rhythms during the orienting response." Brain Research 1232 (September 2008): 163–72. http://dx.doi.org/10.1016/j.brainres.2008.07.030.

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40

Shaman, Jeffrey, and Jonathan F. Day. "Reproductive Phase Locking of Mosquito Populations in Response to Rainfall Frequency." PLoS ONE 2, no. 3 (March 28, 2007): e331. http://dx.doi.org/10.1371/journal.pone.0000331.

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41

Sherman, A., and M. Schreiber. "Low-Frequency Magnetic Response in the Pseudogap Phase of Cuprate Perovskites." Journal of Superconductivity and Novel Magnetism 25, no. 6 (April 21, 2012): 1833–41. http://dx.doi.org/10.1007/s10948-012-1573-6.

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42

Wagner, Hermann, Sandra Brill, Richard Kempter, and Catherine E. Carr. "Auditory Responses in the Barn Owl's Nucleus Laminaris to Clicks: Impulse Response and Signal Analysis of Neurophonic Potential." Journal of Neurophysiology 102, no. 2 (August 2009): 1227–40. http://dx.doi.org/10.1152/jn.00092.2009.

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We used acoustic clicks to study the impulse response of the neurophonic potential in the barn owl's nucleus laminaris. Clicks evoked a complex oscillatory neural response with a component that reflected the best frequency measured with tonal stimuli. The envelope of this component was obtained from the analytic signal created using the Hilbert transform. The time courses of the envelope and carrier waveforms were characterized by fitting them with filters. The envelope was better fitted with a Gaussian than with the envelope of a gamma-tone function. The carrier was better fitted with a frequency glide than with a constant instantaneous frequency. The change of the instantaneous frequency with time was better fitted with a linear fit than with a saturating nonlinearity. Frequency glides had not been observed in the bird's auditory system before. The glides were similar to those observed in the mammalian auditory nerve. Response amplitude, group delay, frequency, and phase depended in a systematic way on click level. In most cases, response amplitude decreased linearly as stimulus level decreased, while group delay, phase, and frequency increased linearly as level decreased. Thus the impulse response of the neurophonic potential in the nucleus laminaris of barn owls reflects many characteristics also observed in responses of the basilar membrane and auditory nerve in mammals.

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43

Schlaghecken, Friederike, and Martin Eimer. "Partial Response Activation to Masked Primes is Not Dependent on Response Readiness." Perceptual and Motor Skills 92, no. 1 (February 2001): 208–22. http://dx.doi.org/10.2466/pms.2001.92.1.208.

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Masked primes presented foveally prior to a target trigger an initial partial activation of their corresponding response, followed by an inhibition of the same response. The latter phase results in performance costs on compatible trials and performance benefits on incompatible trials relative to neutral trials (negative compatibility effect). The present study investigated whether this activation-follow-by-inhibition process depends on the overall or specific state of response readiness. In two masked priming experiments, response readiness was manipulated by varying the relative frequency of Go-trials in a Go/NoGo task (Exp. 1) and the relative frequency of left- and right-hand responses in a 2-alternative choice reaction time task (Exp. 2). In both experiments, mean reaction times were longer for infrequent responses than for frequent responses. However, negative compatibility effects were not affected by response frequency. This result indicates that neither the general ability of masked primes to elicit a partial motor activation nor the specific time course of this process is dependent on response readiness. It is concluded that response readiness affects the execution of an overt response rather than the initial activation of this response.

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44

Krause, Bryan M., and Matthew I. Banks. "Analysis of stimulus-related activity in rat auditory cortex using complex spectral coefficients." Journal of Neurophysiology 110, no. 3 (August 1, 2013): 621–39. http://dx.doi.org/10.1152/jn.00187.2013.

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The neural mechanisms of sensory responses recorded from the scalp or cortical surface remain controversial. Evoked vs. induced response components (i.e., changes in mean vs. variance) are associated with bottom-up vs. top-down processing, but trial-by-trial response variability can confound this interpretation. Phase reset of ongoing oscillations has also been postulated to contribute to sensory responses. In this article, we present evidence that responses under passive listening conditions are dominated by variable evoked response components. We measured the mean, variance, and phase of complex time-frequency coefficients of epidurally recorded responses to acoustic stimuli in rats. During the stimulus, changes in mean, variance, and phase tended to co-occur. After the stimulus, there was a small, low-frequency offset response in the mean and modest, prolonged desynchronization in the alpha band. Simulations showed that trial-by-trial variability in the mean can account for most of the variance and phase changes observed during the stimulus. This variability was state dependent, with smallest variability during periods of greatest arousal. Our data suggest that cortical responses to auditory stimuli reflect variable inputs to the cortical network. These analyses suggest that caution should be exercised when interpreting variance and phase changes in terms of top-down cortical processing.

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45

Tanabe, Seiji, and Bruce G. Cumming. "Delayed suppression shapes disparity selective responses in monkey V1." Journal of Neurophysiology 111, no. 9 (May 1, 2014): 1759–69. http://dx.doi.org/10.1152/jn.00426.2013.

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The stereo correspondence problem poses a challenge to visual neurons because localized receptive fields potentially cause false responses. Neurons in the primary visual cortex (V1) partially resolve this problem by combining excitatory and suppressive responses to encode binocular disparity. We explored the time course of this combination in awake, monkey V1 neurons using subspace mapping of receptive fields. The stimulus was a binocular noise pattern constructed from discrete spatial frequency components. We forward correlated the firing of the V1 neuron with the occurrence of binocular presentations of each spatial frequency component. The forward correlation yielded a complete set of response time courses to every combination of spatial frequency and interocular phase difference. Some combinations produced suppressive responses. Typically, if an interocular phase difference for a given spatial frequency produced strong excitation, we saw suppression in response to the opposite interocular phase difference at lower spatial frequencies. The suppression was delayed relative to the excitation, with a median difference in latency of 7 ms. We found that the suppressive mechanism explains a well-known mismatch of monocular and binocular signals. The suppressive components increased power at low spatial frequencies in disparity tuning, whereas they reduced the monocular response to low spatial frequencies. This long-recognized mismatch of binocular and monocular signals reflects a suppressive mechanism that helps reduce the response to false matches.

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46

White-Schwoch, Travis, Samira Anderson, Jennifer Krizman, Trent Nicol, and Nina Kraus. "Case studies in neuroscience: subcortical origins of the frequency-following response." Journal of Neurophysiology 122, no. 2 (August 1, 2019): 844–48. http://dx.doi.org/10.1152/jn.00112.2019.

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The auditory frequency-following response (FFR) reflects synchronized and phase-locked activity along the auditory pathway in response to sound. Although FFRs were historically thought to reflect subcortical activity, recent evidence suggests an auditory cortex contribution as well. Here we present electrophysiological evidence for the FFR’s origins from two cases: a patient with bilateral auditory cortex lesions and a patient with auditory neuropathy, a condition of subcortical origin. The patient with auditory cortex lesions had robust and replicable FFRs, but no cortical responses. In contrast, the patient with auditory neuropathy had no FFR despite robust and replicable cortical responses. This double dissociation shows that subcortical synchrony is necessary and sufficient to generate an FFR. NEW & NOTEWORTHY The frequency-following response (FFR) reflects synchronized and phase-locked neural activity in response to sound. The authors present a dual case study, comparing FFRs and cortical potentials between a patient with auditory neuropathy (a condition of subcortical origin) and a patient with bilateral auditory cortex lesions. They show that subcortical synchrony is necessary and sufficient to generate an FFR.

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47

Kundu, Bornali, Jeffrey S. Johnson, and Bradley R. Postle. "Prestimulation phase predicts the TMS-evoked response." Journal of Neurophysiology 112, no. 8 (October 15, 2014): 1885–93. http://dx.doi.org/10.1152/jn.00390.2013.

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Анотація:

Prestimulation oscillatory phase and power in particular frequency bands predict perception of at-threshold visual stimuli and of transcranial magnetic stimulation (TMS)-induced phosphenes. These effects may be due to changes in cortical excitability, such that certain ranges of power and/or phase values result in a state in which a particular brain area is more receptive to input, thereby biasing behavior. However, the effects of trial-by-trial fluctuations in phase and power of ongoing oscillations on the brain's electrical response to TMS itself have thus far not been addressed. The present study adopts a combined TMS and electroencepalography (EEG) approach to determine whether the TMS-evoked response is sensitive to momentary fluctuations in prestimulation phase and/or power in different frequency bands. Specifically, TMS was applied to superior parietal lobule while subjects performed a short-term memory task. Results showed that the prestimulation phase, particularly within the beta (15–25 Hz) band, predicted pulse-by-pulse variations in the global mean field amplitude. No such relationship was observed between prestimulation power and the global mean field amplitude. Furthermore, TMS-evoked power in the beta band fluctuated with prestimulation phase in the beta band in a manner that differed from spontaneous brain activity. These effects were observed in areas at and distal to the stimulation site. Together, these results confirm the idea that fluctuating phase of ongoing neuronal oscillations create “windows of excitability” in the brain, and they give insight into how TMS interacts with ongoing brain activity on a pulse-by-pulse basis.

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48

Kaufman, Galen D., Michael E. Shinder, and Adrian A. Perachio. "Convergent Properties of Vestibular-Related Brain Stem Neurons in the Gerbil." Journal of Neurophysiology 83, no. 4 (April 1, 2000): 1958–71. http://dx.doi.org/10.1152/jn.2000.83.4.1958.

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Three classes of vestibular-related neurons were found in and near the prepositus and medial vestibular nuclei of alert or decerebrate gerbils, those responding to: horizontal translational motion, horizontal head rotation, or both. Their distribution ratios were 1:2:2, respectively. Many cells responsive to translational motion exhibited spatiotemporal characteristics with both response gain and phase varying as a function of the stimulus vector angle. Rotationally sensitive neurons were distributed as Type I, II, or III responses (sensitive to ipsilateral, contralateral, or both directions, respectively) in the ratios of 4:6:1. Four tested factors shaped the response dynamics of the sampled neurons: canal-otolith convergence, oculomotor-related activity, rotational Type (I or II), and the phase of the maximum response. Type I nonconvergent cells displayed increasing gains with increasing rotational stimulus frequency (0.1–2.0 Hz, 60°/s), whereas Type II neurons with convergent inputs had response gains that markedly decreased with increasing translational stimulus frequency (0.25–2.0 Hz, ±0.1 g). Type I convergent and Type II nonconvergent neurons exhibited essentially flat gains across the stimulus frequency range. Oculomotor-related activity was noted in 30% of the cells across all functional types, appearing as burst/pause discharge patterns related to the fast phase of nystagmus during head rotation. Oculomotor-related activity was correlated with enhanced dynamic range compared with the same category that had no oculomotor-related response. Finally, responses that were in-phase with head velocity during rotation exhibited greater gains with stimulus frequency increments than neurons with out-of-phase responses. In contrast, for translational motion, neurons out of phase with head acceleration exhibited low-pass characteristics, whereas in-phase neurons did not. Data from decerebrate preparations revealed that although similar response types could be detected, the sampled cells generally had lower background discharge rates, on average one-third lower response gains, and convergent properties that differed from those found in the alert animals. On the basis of the dynamic response of identified cell types, we propose a pair of models in which inhibitory input from vestibular-related neurons converges on oculomotor neurons with excitatory inputs from the vestibular nuclei. Simple signal convergence and combinations of different types of vestibular labyrinth information can enrich the dynamic characteristics of the rotational and translational vestibuloocular responses.

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49

Siebold, C., J. F. Kleine, L. Glonti, T. Tchelidze, and U. Büttner. "Fastigial Nucleus Activity During Different Frequencies and Orientations of Vertical Vestibular Stimulation in the Monkey." Journal of Neurophysiology 82, no. 1 (July 1, 1999): 34–41. http://dx.doi.org/10.1152/jn.1999.82.1.34.

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Neurons in the rostral part of the fastigial nucleus (FN) respond to vestibular stimulation but are not related to eye movements. To understand the precise role of these vestibular-only neurons in the central processing of vestibular signals, unit activity in the FN of alert monkeys ( Macaca mulatta) was recorded. To induce vestibular stimulation, the monkey was rotated sinusoidally around an earth-fixed horizontal axis at stimulus frequencies between 0.06 (±15°) and 1.4 Hz (±7.5°). During stimulation head orientation was changed continuously, allowing for roll, pitch, and intermediate planes of orientation. At a frequency of 0.6 Hz, 59% of the neurons had an optimal response orientation (ORO) and a null response (i.e., no modulation) 90° apart. The phase of neuronal response was constant except for a steep shift of 180° around the null response. This group I response is compatible with a semicircular canal input, canal convergence, or a single otolith input. Several other features indicated more complex responses, including spatiotemporal convergence (STC). 1) For 35% of the responses at 0.6 Hz, phase changes were gradual with different orientations. Fifteen percent of these had a null response (group II), and 20% showed only a minimal response but no null response (group III). The remaining responses (6%), classified as group IV, were characterized by a constant sensitivity at different orientations in most instances. 2) For the vast majority of neurons, the stimulus frequency determined the response group, i.e., an individual neuron could show a group I response at one frequency and a group II (III or IV) response at another frequency. 3) ORO changed with frequency by >45° for 44% of the neurons. 4) Although phase changes at different frequencies were close to head velocity (±45°) or head position (±45°) for most neurons, they exceeded 90° for 29% of the neurons between 0.1 and 1.0 Hz. In most cases, this was a phase advance. The change in sensitivity with change in frequency showed a similar pattern for all neurons; the average sensitivity increased from 1.24 imp · s−1 · deg−1 at 0.1 Hz to 2.97 imp · s−1· deg−1 at 1.0 Hz. These data demonstrate that only an analysis based on measurements at different frequencies and orientations reveals a number of complex features. They moreover suggest that for the vast majority of neurons several sources of canal and otolith information interact at this central stage of vestibular information processing.

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50

Banfi, Francesco, and Gabriele Ferrini. "Wavelet cross-correlation and phase analysis of a free cantilever subjected to band excitation." Beilstein Journal of Nanotechnology 3 (March 29, 2012): 294–300. http://dx.doi.org/10.3762/bjnano.3.33.

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This work introduces the concept of time–frequency map of the phase difference between the cantilever response signal and the driving signal, calculated with a wavelet cross-correlation technique. The wavelet cross-correlation quantifies the common power and the relative phase between the response of the cantilever and the exciting driver, yielding “instantaneous” information on the driver-response phase delay as a function of frequency. These concepts are introduced through the calculation of the response of a free cantilever subjected to continuous and impulsive excitation over a frequency band.

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