901 resultados para Discrete Time Domain


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Queueing systems constitute a central tool in modeling and performance analysis. These types of systems are in our everyday life activities, and the theory of queueing systems was developed to provide models for forecasting behaviors of systems subject to random demand. The practical and useful applications of the discrete-time queues make the researchers to con- tinue making an e ort in analyzing this type of models. Thus the present contribution relates to a discrete-time Geo/G/1 queue in which some messages may need a second service time in addition to the rst essential service. In day-to-day life, there are numerous examples of queueing situations in general, for example, in manufacturing processes, telecommunication, home automation, etc, but in this paper a particular application is the use of video surveil- lance with intrusion recognition where all the arriving messages require the main service and only some may require the subsidiary service provided by the server with di erent types of strategies. We carry out a thorough study of the model, deriving analytical results for the stationary distribution. The generating functions of the number of messages in the queue and in the system are obtained. The generating functions of the busy period as well as the sojourn times of a message in the server, the queue and the system are also provided.

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Traditionally, densities of newly built roadways are checked by direct sampling (cores) or by nuclear density gauge measurements. For roadway engineers, density of asphalt pavement surfaces is essential to determine pavement quality. Unfortunately, field measurements of density by direct sampling or by nuclear measurement are slow processes. Therefore, I have explored the use of rapidly-deployed ground penetrating radar (GPR) as an alternative means of determining pavement quality. The dielectric constant of pavement surface may be a substructure parameter that correlates with pavement density, and can be used as a proxy when density of asphalt is not known from nuclear or destructive methods. The dielectric constant of the asphalt can be determined using ground penetrating radar (GPR). In order to use GPR for evaluation of road surface quality, the relationship between dielectric constants of asphalt and their densities must be established. Field measurements of GPR were taken at four highway sites in Houghton and Keweenaw Counties, Michigan, where density values were also obtained using nuclear methods in the field. Laboratory studies involved asphalt samples taken from the field sites and samples created in the laboratory. These were tested in various ways, including, density, thickness, and time domain reflectometry (TDR). In the field, GPR data was acquired using a 1000 MHz air-launched unit and a ground-coupled unit at 200 and 500 MHz. The equipment used was owned and operated by the Michigan Department of Transportation (MDOT) and available for this study for a total of four days during summer 2005 and spring 2006. The analysis of the reflected waveforms included “routine” processing for velocity using commercial software and direct evaluation of reflection coefficients to determine a dielectric constant. The dielectric constants computed from velocities do not agree well with those obtained from reflection coefficients. Perhaps due to the limited range of asphalt types studied, no correlation between density and dielectric constant was evident. Laboratory measurements were taken with samples removed from the field and samples created for this study. Samples from the field were studied using TDR, in order to obtain dielectric constant directly, and these correlated well with the estimates made from reflection coefficients. Samples created in the laboratory were measured using 1000 MHz air-launched GPR, and 400 MHz ground-coupled GPR, each under both wet and dry conditions. On the basis of these observations, I conclude that dielectric constant of asphalt can be reliably measured from waveform amplitude analysis of GJPR data, based on the consistent agreement with that obtained in the laboratory using TDR. Because of the uniformity of asphalts studied here, any correlation between dielectric constant and density is not yet apparent.

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In this paper, we develop a new family of graph kernels where the graph structure is probed by means of a discrete-time quantum walk. Given a pair of graphs, we let a quantum walk evolve on each graph and compute a density matrix with each walk. With the density matrices for the pair of graphs to hand, the kernel between the graphs is defined as the negative exponential of the quantum Jensen–Shannon divergence between their density matrices. In order to cope with large graph structures, we propose to construct a sparser version of the original graphs using the simplification method introduced in Qiu and Hancock (2007). To this end, we compute the minimum spanning tree over the commute time matrix of a graph. This spanning tree representation minimizes the number of edges of the original graph while preserving most of its structural information. The kernel between two graphs is then computed on their respective minimum spanning trees. We evaluate the performance of the proposed kernels on several standard graph datasets and we demonstrate their effectiveness and efficiency.

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Recent marine long-offset transient electromagnetic (LOTEM) measurements yielded the offshore delineation of a fresh groundwater body beneath the seafloor in the region of Bat Yam, Israel. The LOTEM application was effective in detecting this freshwater body underneath the Mediterranean Sea and allowed an estimation of its seaward extent. However, the measured data set was insufficient to understand the hydrogeological configuration and mechanism controlling the occurrence of this fresh groundwater discovery. Especially the lateral geometry of the freshwater boundary, important for the hydrogeological modelling, could not be resolved. Without such an understanding, a rational management of this unexploited groundwater reservoir is not possible. Two new high-resolution marine time-domain electromagnetic methods are theoretically developed to derive the hydrogeological structure of the western aquifer boundary. The first is called Circular Electric Dipole (CED). It is the land-based analogous of the Vertical Electric Dipole (VED), which is commonly applied to detect resistive structures in the subsurface. Although the CED shows exceptional detectability characteristics in the step-off signal towards the sub-seafloor freshwater body, an actual application was not carried out in the extent of this study. It was found that the method suffers from an insufficient signal strength to adequately delineate the resistive aquifer under realistic noise conditions. Moreover, modelling studies demonstrated that severe signal distortions are caused by the slightest geometrical inaccuracies. As a result, a successful application of CED in Israel proved to be rather doubtful. A second method called Differential Electric Dipole (DED) is developed as an alternative to the intended CED method. Compared to the conventional marine time-domain electromagnetic system that commonly applies a horizontal electric dipole transmitter, the DED is composed of two horizontal electric dipoles in an in-line configuration that share a common central electrode. Theoretically, DED has similar detectability/resolution characteristics compared to the conventional LOTEM system. However, the superior lateral resolution towards multi-dimensional resistivity structures make an application desirable. Furthermore, the method is less susceptible towards geometrical errors making an application in Israel feasible. In the extent of this thesis, the novel marine DED method is substantiated using several one-dimensional (1D) and multi-dimensional (2D/3D) modelling studies. The main emphasis lies on the application in Israel. Preliminary resistivity models are derived from the previous marine LOTEM measurement and tested for a DED application. The DED method is effective in locating the two-dimensional resistivity structure at the western aquifer boundary. Moreover, a prediction regarding the hydrogeological boundary conditions are feasible, provided a brackish water zone exists at the head of the interface. A seafloor-based DED transmitter/receiver system is designed and built at the Institute of Geophysics and Meteorology at the University of Cologne. The first DED measurements were carried out in Israel in April 2016. The acquired data set is the first of its kind. The measured data is processed and subsequently interpreted using 1D inversion. The intended aim of interpreting both step-on and step-off signals failed, due to the insufficient data quality of the latter. Yet, the 1D inversion models of the DED step-on signals clearly detect the freshwater body for receivers located close to the Israeli coast. Additionally, a lateral resistivity contrast is observable in the 1D inversion models that allow to constrain the seaward extent of this freshwater body. A large-scale 2D modelling study followed the 1D interpretation. In total, 425 600 forward calculations are conducted to find a sub-seafloor resistivity distribution that adequately explains the measured data. The results indicate that the western aquifer boundary is located at 3600 m - 3700 m before the coast. Moreover, a brackish water zone of 3 Omega*m to 5 Omega*m with a lateral extent of less than 300 m is likely located at the head of the freshwater aquifer. Based on these results, it is predicted that the sub-seafloor freshwater body is indeed open to the sea and may be vulnerable to seawater intrusion.

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A simple method to generate time domain tailored waveforms for excitation of ion axial amplitude in Paul trap mass spectrometers is described. The method is based on vector summation of sine waves followed by time domain sampling to obtain the discrete time domain data. A smoothing technique based on the time domain Kaiser window is then applied to the data so as to minimize the frequency domain Gibb's oscillations. The dynamic range of the time domain signal is controlled by phase modulation and time extension of the time domain waveform. Copyright (C) 1999 John Wiley & Sons, Ltd.

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Department of Statistics, Cochin University of Sciene ans Technology

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The water time constant and mechanical time constant greatly influences the power and speed oscillations of hydro-turbine-generator unit. This paper discusses the turbine power transients in response to different nature and changes in the gate position. The work presented here analyses the characteristics of hydraulic system with an emphasis on changes in the above time constants. The simulation study is based on mathematical first-, second-, third- and fourth-order transfer function models. The study is further extended to identify discrete time-domain models and their characteristic representation without noise and with noise content of 10 & 20 dB signal-to-noise ratio (SNR). The use of self-tuned control approach in minimising the speed deviation under plant parameter changes and disturbances is also discussed.

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Two direct sampling correlator-type receivers for differential chaos shift keying (DCSK) communication systems under frequency non-selective fading channels are proposed. These receivers operate based on the same hardware platform with different architectures. In the first scheme, namely sum-delay-sum (SDS) receiver, the sum of all samples in a chip period is correlated with its delayed version. The correlation value obtained in each bit period is then compared with a fixed threshold to decide the binary value of recovered bit at the output. On the other hand, the second scheme, namely delay-sum-sum (DSS) receiver, calculates the correlation value of all samples with its delayed version in a chip period. The sum of correlation values in each bit period is then compared with the threshold to recover the data. The conventional DCSK transmitter, frequency non-selective Rayleigh fading channel, and two proposed receivers are mathematically modelled in discrete-time domain. The authors evaluated the bit error rate performance of the receivers by means of both theoretical analysis and numerical simulation. The performance comparison shows that the two proposed receivers can perform well under the studied channel, where the performances get better when the number of paths increases and the DSS receiver outperforms the SDS one.

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The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the in influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.

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The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.

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Diagnostics of rotating machinery has developed significantly in the last decades, and industrial applications are spreading in different sectors. Most applications are characterized by varying velocities of the shaft and in many cases transients are the most critical to monitor. In these variable speed conditions, fault symptoms are clearer in the angular/order domains than in the common time/frequency ones. In the past, this issue was often solved by synchronously sampling data by means of phase locked circuits governing the acquisition; however, thanks to the spread of cheap and powerful microprocessors, this procedure is nowadays rarer; sampling is usually performed at constant time intervals, and the conversion to the order domain is made by means of digital signal processing techniques. In the last decades different algorithms have been proposed for the extraction of an order spectrum from a signal sampled asynchronously with respect to the shaft rotational velocity; many of them (the so called computed order tracking family) use interpolation techniques to resample the signal at constant angular increments, followed by a common discrete Fourier transform to shift from the angular domain to the order domain. A less exploited family of techniques shifts directly from the time domain to the order spectrum, by means of modified Fourier transforms. This paper proposes a new transform, named velocity synchronous discrete Fourier transform, which takes advantage of the instantaneous velocity to improve the quality of its result, reaching performances that can challenge the computed order tracking.

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The transmission path from the excitation to the measured vibration on the surface of a mechanical system introduces a distortion both in amplitude and in phase. Moreover, in variable speed conditions, the amplification/attenuation and the phase shift, due to the transfer function of the mechanical system, varies in time. This phenomenon reduces the effectiveness of the traditionally tachometer based order tracking, compromising the results of a discrete-random separation performed by a synchronous averaging. In this paper, for the first time, the extent of the distortion is identified both in the time domain and in the order spectrum of the signal, highlighting the consequences for the diagnostics of rotating machinery. A particular focus is given to gears, providing some indications on how to take advantage of the quantification of the disturbance to better tune the techniques developed for the compensation of the distortion. The full theoretical analysis is presented and the results are applied to an experimental case.

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The dynamics describing the motion response of a marine structure in waves can be represented within a linear framework by the Cummins Equation. This equation contains a convolution term that represents the component of the radiation forces associated with fluid memory effects. Several methods have been proposed in the literature for the identification of parametric models to approximate and replace this convolution term. This replacement can facilitate the model implementation in simulators and the analysis of motion control designs. Some of the reported identification methods consider the problem in the time domain while other methods consider the problem in the frequency domain. This paper compares the application of these identification methods. The comparison is based not only on the quality of the estimated models, but also on the ease of implementation, ease of use, and the flexibility of the identification method to incorporate prior information related to the model being identified. To illustrate the main points arising from the comparison, a particular example based on the coupled vertical motion of a modern containership vessel is presented.

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In this paper, we present a new speech enhancement approach, that is based on exploiting the intra-frame dependency of discrete cosine transform (DCT) domain coefficients. It can be noted that the existing enhancement techniques treat the transformdomain coefficients independently. Instead of this traditional approach of independently processing the scalars, we split the DCT domain noisy speech vector into sub-vectors and each sub-vector is enhanced independently. Through this sub-vector based approach, the higher dimensional enhancement advantage, viz. non-linear dependency, is exploited. In the developed method, each clean speech sub-vector is modeled using a Gaussian mixture (GM) density. We show that the proposed Gaussian mixture model (GMM) based DCT domain method, using sub-vector processing approach, provides better performance than the conventional approach of enhancing the transform domain scalar components independently. Performance improvement over the recently proposed GMM based time domain approach is also shown.

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The propagation of axial waves in hyperelastic rods is studied using both time and frequency domain finite element models. The nonlinearity is introduced using the Murnaghan strain energy function and the equations governing the dynamics of the rod are derived assuming linear kinematics. In the time domain, the standard Galerkin finite element method, spectral element method, and Taylor-Galerkin finite element method are considered. A frequency domain formulation based on the Fourier spectral method is also developed. It is found that the time domain spectral element method provides the most efficient numerical tool for the problem considered.