942 resultados para Time and frequency autocorrelation


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Turning points for transitions between the electrostatic and electromagnetic discharge modes in low-frequency (∼ 500 kHz) inductively coupled plasmas have been identified and cross-referenced using time-resolved measurements of the plasma optical emission intensities, RF coil current, and ion saturation current collected by a single RF-compensated Langmuir probe. This enables one to monitor the variation of the plasma parameters, power transfer efficiency, which accompany the discharge hysteresis. The excitation conditions for the pure and hybrid modes in the plasma are considered, and the possibility of the TMmnl → TEm'n'l' transitions at higher frequencies are discussed.

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The electrical and optical response of a field-effect device comprising a network of semiconductor-enriched single-wall carbon nanotubes, gated with sodium chloride solution is investigated. Field-effect is demonstrated in a device that uses facile fabrication techniques along with a small-ion as the gate electrolyte-and this is accomplished as a result of the semiconductor enhancement of the tubes. The optical transparency and electrical resistance of the device are modulated with gate voltage. A time-response study of the modulation of optical transparency and electrical resistance upon application of gate voltage suggests the percolative charge transport in the network. Also the ac response in the network is investigated as a function of frequency and temperature down to 5 K. An empirical relation between onset frequency and temperature is determined.

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Research has been undertaken to ascertain the predictability of non-stationary time series using wavelet and Empirical Mode Decomposition (EMD) based time series models. Methods have been developed in the past to decompose a time series into components. Forecasting of these components combined with random component could yield predictions. Using this ideology, wavelet and EMD analyses have been incorporated separately which decomposes a time series into independent orthogonal components with both time and frequency localizations. The component series are fit with specific auto-regressive models to obtain forecasts which are later combined to obtain the actual predictions. Four non-stationary streamflow sites (USGS data resources) of monthly total volumes and two non-stationary gridded rainfall sites (IMD) of monthly total rainfall are considered for the study. The predictability is checked for six and twelve months ahead forecasts across both the methodologies. Based on performance measures, it is observed that wavelet based method has better prediction capabilities over EMD based method despite some of the limitations of time series methods and the manner in which decomposition takes place. Finally, the study concludes that the wavelet based time series algorithm can be used to model events such as droughts with reasonable accuracy. Also, some modifications that can be made in the model have been discussed that could extend the scope of applicability to other areas in the field of hydrology. (C) 2013 Elesvier B.V. All rights reserved.

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Phase-locked loops (PLLs) are necessary in grid connected systems to obtain information about the frequency, amplitude and phase of the grid voltage. In stationary reference frame control, the unit vectors of PLLs are used for reference generation. It is important that the PLL performance is not affected significantly when grid voltage undergoes amplitude and frequency variations. In this paper, a novel design for the popular single-phase PLL topology, namely the second-order generalized integrator (SOGI) based PLL is proposed which achieves minimum settling time during grid voltage amplitude and frequency variations. The proposed design achieves a settling time of less than 27.7 ms. This design also ensures that the unit vectors generated by this PLL have a steady state THD of less than 1% during frequency variations of the grid voltage. The design of the SOGI-PLL based on the theoretical analysis is validated by experimental results.

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The response of linear, viscous damped systems to excitations having time-varying frequency is the subject of exact and approximate analyses, which are supplemented by an analog computer study of single degree of freedom system response to excitations having frequencies depending linearly and exponentially on time.

The technique of small perturbations and the methods of stationary phase and saddle-point integration, as well as a novel bounding procedure, are utilized to derive approximate expressions characterizing the system response envelope—particularly near resonances—for the general time-varying excitation frequency.

Descriptive measurements of system resonant behavior recorded during the course of the analog study—maximum response, excitation frequency at which maximum response occurs, and the width of the response peak at the half-power level—are investigated to determine dependence upon natural frequency, damping, and the functional form of the excitation frequency.

The laboratory problem of determining the properties of a physical system from records of its response to excitations of this class is considered, and the transient phenomenon known as “ringing” is treated briefly.

It is shown that system resonant behavior, as portrayed by the above measurements and expressions, is relatively insensitive to the specifics of the excitation frequency-time relation and may be described to good order in terms of parameters combining system properties with the time derivative of excitation frequency evaluated at resonance.

One of these parameters is shown useful for predicting whether or not a given excitation having a time-varying frequency will produce strong or subtle changes in the response envelope of a given system relative to the steady-state response envelope. The parameter is shown, additionally, to be useful for predicting whether or not a particular response record will exhibit the “ringing” phenomenon.

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A number of recent scientific and engineering problems require signals to be decomposed into a product of a slowly varying positive envelope and a quickly varying carrier whose instantaneous frequency also varies slowly over time. Although signal processing provides algorithms for so-called amplitude-and frequency-demodulation (AFD), there are well known problems with all of the existing methods. Motivated by the fact that AFD is ill-posed, we approach the problem using probabilistic inference. The new approach, called probabilistic amplitude and frequency demodulation (PAFD), models instantaneous frequency using an auto-regressive generalization of the von Mises distribution, and the envelopes using Gaussian auto-regressive dynamics with a positivity constraint. A novel form of expectation propagation is used for inference. We demonstrate that although PAFD is computationally demanding, it outperforms previous approaches on synthetic and real signals in clean, noisy and missing data settings.

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This paper presents a long range and effectively error-free ultra high frequency (UHF) radio frequency identification (RFID) interrogation system. The system is based on a novel technique whereby two or more spatially separated transmit and receive antennas are used to enable greatly enhanced tag detection performance over longer distances using antenna diversity combined with frequency and phase hopping. The novel technique is first theoretically modelled using a Rician fading channel. It is shown that conventional RFID systems suffer from multi-path fading resulting in nulls in radio environments. We, for the first time, demonstrate that the nulls can be moved around by varying the phase and frequency of the interrogation signals in a multi-antenna system. As a result, much enhanced coverage can be achieved. A proof of principle prototype RFID system is built based on an Impinj R2000 transceiver. The demonstrator system shows that the new approach improves the tag detection accuracy from <50% to 100% and the tag backscatter signal strength by 10dB over a 20 m x 9 m area, compared with a conventional switched multi-antenna RFID system.

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This work addresses two related questions. The first question is what joint time-frequency energy representations are most appropriate for auditory signals, in particular, for speech signals in sonorant regions. The quadratic transforms of the signal are examined, a large class that includes, for example, the spectrograms and the Wigner distribution. Quasi-stationarity is not assumed, since this would neglect dynamic regions. A set of desired properties is proposed for the representation: (1) shift-invariance, (2) positivity, (3) superposition, (4) locality, and (5) smoothness. Several relations among these properties are proved: shift-invariance and positivity imply the transform is a superposition of spectrograms; positivity and superposition are equivalent conditions when the transform is real; positivity limits the simultaneous time and frequency resolution (locality) possible for the transform, defining an uncertainty relation for joint time-frequency energy representations; and locality and smoothness tradeoff by the 2-D generalization of the classical uncertainty relation. The transform that best meets these criteria is derived, which consists of two-dimensionally smoothed Wigner distributions with (possibly oriented) 2-D guassian kernels. These transforms are then related to time-frequency filtering, a method for estimating the time-varying 'transfer function' of the vocal tract, which is somewhat analogous to ceptstral filtering generalized to the time-varying case. Natural speech examples are provided. The second question addressed is how to obtain a rich, symbolic description of the phonetically relevant features in these time-frequency energy surfaces, the so-called schematic spectrogram. Time-frequency ridges, the 2-D analog of spectral peaks, are one feature that is proposed. If non-oriented kernels are used for the energy representation, then the ridge tops can be identified, with zero-crossings in the inner product of the gradient vector and the direction of greatest downward curvature. If oriented kernels are used, the method can be generalized to give better orientation selectivity (e.g., at intersecting ridges) at the cost of poorer time-frequency locality. Many speech examples are given showing the performance for some traditionally difficult cases: semi-vowels and glides, nasalized vowels, consonant-vowel transitions, female speech, and imperfect transmission channels.

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A method for measuring the phase of oscillations from noisy time series is proposed. To obtain the phase, the signal is filtered in such a way that the filter output has minimal relative variation in the amplitude over all filters with complex-valued impulse response. The argument of the filter output yields the phase. Implementation of the algorithm and interpretation of the result are discussed. We argue that the phase obtained by the proposed method has a low susceptibility to measurement noise and a low rate of artificial phase slips. The method is applied for the detection and classification of mode locking in vortex flow meters. A measure for the strength of mode locking is proposed.

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Across languages, children with developmental dyslexia have a specific difficulty with the neural representation of the sound structure (phonological structure) of speech. One likely cause of their difficulties with phonology is a perceptual difficulty in auditory temporal processing (Tallal, 1980). Tallal (1980) proposed that basic auditory processing of brief, rapidly successive acoustic changes is compromised in dyslexia, thereby affecting phonetic discrimination (e.g. discriminating /b/ from /d/) via impaired discrimination of formant transitions (rapid acoustic changes in frequency and intensity). However, an alternative auditory temporal hypothesis is that the basic auditory processing of the slower amplitude modulation cues in speech is compromised (Goswami , 2002). Here, we contrast children's perception of a synthetic speech contrast (ba/wa) when it is based on the speed of the rate of change of frequency information (formant transition duration) versus the speed of the rate of change of amplitude modulation (rise time). We show that children with dyslexia have excellent phonetic discrimination based on formant transition duration, but poor phonetic discrimination based on envelope cues. The results explain why phonetic discrimination may be allophonic in developmental dyslexia (Serniclaes , 2004), and suggest new avenues for the remediation of developmental dyslexia. © 2010 Blackwell Publishing Ltd.

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The theory of fractional calculus (FC) is a useful mathematical tool in many applied sciences. Nevertheless, only in the last decades researchers were motivated for the adoption of the FC concepts. There are several reasons for this state of affairs, namely the co-existence of different definitions and interpretations, and the necessity of approximation methods for the real time calculation of fractional derivatives (FDs). In a first part, this paper introduces a probabilistic interpretation of the fractional derivative based on the Grünwald-Letnikov definition. In a second part, the calculation of fractional derivatives through Padé fraction approximations is analyzed. It is observed that the probabilistic interpretation and the frequency response of fraction approximations of FDs reveal a clear correlation between both concepts.

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Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation. Current implementations of these functions rely on conventional techniques largely based on Fourier Techniques, primarily meant for stationary signals. Interestingly enough, the signals received by the sonar sensors are often non-stationary and hence processing methods capable of handling the non-stationarity will definitely fare better than Fourier transform based methods.Time-frequency methods(TFMs) are known as one of the best DSP tools for nonstationary signal processing, with which one can analyze signals in time and frequency domains simultaneously. But, other than STFT, TFMs have been largely limited to academic research because of the complexity of the algorithms and the limitations of computing power. With the availability of fast processors, many applications of TFMs have been reported in the fields of speech and image processing and biomedical applications, but not many in sonar processing. A structured effort, to fill these lacunae by exploring the potential of TFMs in sonar applications, is the net outcome of this thesis. To this end, four TFMs have been explored in detail viz. Wavelet Transform, Fractional Fourier Transfonn, Wigner Ville Distribution and Ambiguity Function and their potential in implementing five major sonar functions has been demonstrated with very promising results. What has been conclusively brought out in this thesis, is that there is no "one best TFM" for all applications, but there is "one best TFM" for each application. Accordingly, the TFM has to be adapted and tailored in many ways in order to develop specific algorithms for each of the applications.

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We use Hasbrouck's (1991) vector autoregressive model for prices and trades to empirically test and assess the role played by the waiting time between consecutive transactions in the process of price formation. We find that as the time duration between transactions decreases, the price impact of trades, the speed of price adjustment to trade‐related information, and the positive autocorrelation of signed trades all increase. This suggests that times when markets are most active are times when there is an increased presence of informed traders; we interpret such markets as having reduced liquidity.

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This paper presents a new method for blind source separation by exploiting phase and frequency redundancy of cyclostationary signals in a complementary way. It requires a weaker separation condition than those methods which only exploit the phase diversity or the frequency diversity of the source signals. The separation criterion is to diagonalize a polynomial matrix whose coefficient matrices consist of the correlation and cyclic correlation matrices, at time delay .TAU. = 0, of multiple measurements. An algorithm is proposed to perform the blind source separation. Computer simulation results illustrate the performance of the new algorithm in comparison with the existing ones.

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Temperature changes in conducting polypyrrole/para-toluene-2-sulphonic acid (PPy/pTSA) coated nylon textiles due to microwave absorption in the 8–9 GHz and 15–16 GHz frequency ranges were obtained by a thermography station during simultaneous irradiation of the samples. The temperature values are compared and related to the amounts of reflection, transmission and absorption obtained with a non-contact free space transmission technique, indicating a relationship between microwave absorption and temperature increase. Non-conductive samples showed no temperature increase upon irradiation irrespective of frequency range. The maximum temperature difference of around 4 °C in the conducting fabrics relative to ambient temperature was observed in samples having 48% absorption and 26.5 ± 4% reflection. Samples polymerized for 60 or 120 min with a dopant concentration of 0.018 mol/l or polymerized for 180 min with a dopant concentration of 0.009 mol/l yielded optimum absorption levels. As the surface resistivity decreased and the reflection levels increased, the temperature increase upon irradiation reduced.