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Recently, we proposed a Spectral Domain Sparse Representation (SDSR) approach for the direction-of-arrival estimation of signals incident to an antenna array. In the approach, sparse representation is applied to the conventional Bartlett spectra obtained from snapshots of the signals received by the antenna array to increase the direction-of-arrival (DOA) estimation resolution and accuracy. The conventional Bartlett spectra has limited dynamic range, meaning that one may not be able to identify the presence of weak signals in the presence of strong signals. This is because, in the conventional Bartlett spectra, uniform weighting (window) is applied to signals received by various antenna elements. Apodization can be used in the generation of Bartlett spectra to increase the dynamic range of the spectra. In Apodization, more than one window function is used to generate different portions of the spectra. In this paper, we extend the SDSR approach to include Bartlett spectra obtained with Apodization and to evaluate the performance of the extended SDSR approach. We compare its performance with a two-step SDSR approach and with an approach where Bartlett spectra is obtained using a low sidelobe window function. We show that an Apodization Bartlett-based SDSR approach leads to better performance with just single-step processing.

This work studies the application of short-time Fourier transform (STFT) to extract current harmonics of various fault types to design a protection method for meshed multi-terminal voltage source converter-high-voltage direct current (VSC-HVDC-MTDC) grids. The frequency spectrum of fault current harmonics is used to detect internal and external faults, the faulty pole and fault type. The method does not need the implementation of series inductance on the sides of the DC lines and it is also effective for lines combining overhead lines and cables. The window function and hop size play the primary role in STFT, which are investigated in a sensitivity analysis. A modified version of CIGRE meshed DC grid system is simulated in PSCAD in order to show the robustness of the method, and further signal processing analysis is done in MATLAB. The results show the accurate detection and discrimination between faulty sections using the proposed harmonic-based method and how important the STFT parameters are in order to have a robust protection algorithm.

Surface profile is one of the key evaluation indexes in the optical industry. With the development of optical technology, wavelength-tuned phase-shifting interferometry has been widely used for measuring the surface profiles of optical components based on the high accuracy of this technique. However, coupling errors caused by higher harmonics and phase-shift errors may lead to systematic errors in the calculated phase. In this research, to suppress coupling errors effectively, we propose an 8N - 7 phase-shifting algorithm consisting of a novel polynomial window function and discrete Fourier transform. By locating eight multiple roots on the characteristic diagram, the polynomial window function of the proposed algorithm is derived based on the theory of characteristic polynomials. The characteristic polynomial of the 8N - 7 algorithm is estimated based on a Fourier representation. Phase errors are discussed and compared to the errors in other algorithms. The results indicate that the 8N - 7 algorithm has the smallest phase error among the compared algorithms and can compensate for up to sixth-order nonlinearity in phase measurements. Finally, the proposed algorithm was applied to profile the surface of a silicon wafer. The results revealed that the standard deviation across 20 experiments was 3.231 nm, which is much smaller than the standard deviations of conventional phase-shifting algorithms. [ABSTRACT FROM AUTHOR]

To improve the effectiveness of memristor model in complex network, the drift model of memristor is further optimized. In this paper, based on both the existing nonlinear doping kinetic model and sinusoidal function, a new model is proposed, which agrees with the five criteria for describing the migration characteristics of nonlinear dopant. Secondly, to improve the flexibility of the new model, two in-built control parameters are introduced, and it is verified by using the coupled variable-resistor model proposed by HP research team. The simulation results show that the new model is well matched with the authoritative memristor model. At the same time, by constructing the Simulink model of memristor we have verified the effectiveness of the new model. Finally, the new model is applied to the three-node Hopfield neural network, and the dynamic behaviors of this network have been investigated. In particular, we have introduced an electromagnetic induction coefficient to describe the possible electromagnetic field effect caused by signal transmission in the network. The results will provide a new idea for the memristor to be widely used in complex network, artificial synapse and many other fields. [ABSTRACT FROM AUTHOR]

Memristors have become promising candidates for the advancement of recent technology as the miniaturization of complementary metal–oxide–semiconductor (CMOS) technology approaches its final stage. Nanoscale size, easy fabrication, compatibility with MOS, and diverse applications have accelerated these devices to new levels. In this paper, we discuss the merits and demerits of existing window functions and propose a novel window function that addresses their limitations. The suggested window function exhibits high nonlinearity at the boundaries and resolves other boundary issues. The results obtained using the proposed window function are compared with data reported in the literature to validate our design approach. [ABSTRACT FROM AUTHOR]

Convolution sum system representations are commonly used in signal processing. It is known that the convolution sum, treated as the limit of its partial sums, can be divergent for certain continuous signals and stable linear time-invariant (LTI) systems, even when the convergence of the partial sums is treated in a distributional setting. In this paper, we ask a far more general question: is it at all possible to define a generalized convolution sum with natural properties that works for all absolutely integrable continuous signals that vanish at infinity and all stable LTI systems? We prove that the answer is “no.” Further, for certain subspaces, we give a sufficient and necessary condition for uniform convergence. Finally, we discuss the implications of our results on the effectiveness of window functions in the convolution sum. [ABSTRACT FROM AUTHOR]

Abstract Dynamic electrochemical impedance spectroscopy (DEIS) has attracted the interest of researchers due to its capability of acquiring impedance spectra of non-stationary systems in a broad range of frequencies. Although developed in the 70's, a physical definition of dynamic impedance, and in general of dynamic transfer function, is not present in literature. In this manuscript the general concept of dynamic frequency response is given in correlation to the Volterra series expansion: this can be used to define the ideal dynamic impedance response of an electrochemical system. It is clarified that DEIS is the intermodulation of the ac signal with the dc signal. Starting from this, different strategies for the extraction of the dynamic impedance spectra are compared, which are based on different heuristic definitions of DEIS. There are two main methodologies, one based on the use of window functions and the other on quadrature filters. Limits and merits of the different methodologies are discussed in the frame of the data analysis and data handling and show that window functions suffers at recovering low-frequencies impedances while quadrature filters work best in experiments which have a periodic or quasi-periodic trend. [ABSTRACT FROM AUTHOR]

Apodization weighted acquisition is a simple approach to enhance the sensitivity of multidimensional NMR spectra by scaling the number of scans during acquisition of the indirect dimension(s). The signal content of the resulting spectra is identical to conventionally sampled data, yet the spectra show improved signal-to-noise ratios. There are no special requirements for data acquisition and processing: the time-domain data can be transformed with the same schemes used for conventionally recorded spectra, including Fourier transformation. The method is of general use in multidimensional liquid and solid state NMR experiments if the number of recorded transients per sampling point is bigger than the minimum required phase cycle of the pulse sequence. [ABSTRACT FROM AUTHOR]

This work studies the application of short-time Fourier transform (STFT) to extract current harmonics of various fault types to design a protection method for meshed multi-terminal voltage source converter-high-voltage direct current (VSC-HVDC-MTDC) grids. The frequency spectrum of fault current harmonics is used to detect internal and external faults, the faulty pole and fault type. The method does not need the implementation of series inductance on the sides of the DC lines and it is also effective for lines combining overhead lines and cables. The window function and hop size play the primary role in STFT, which are investigated in a sensitivity analysis. A modified version of CIGRE meshed DC grid system is simulated in PSCAD in order to show the robustness of the method, and further signal processing analysis is done in MATLAB. The results show the accurate detection and discrimination between faulty sections using the proposed harmonic-based method and how important the STFT parameters are in order to have a robust protection algorithm. [ABSTRACT FROM AUTHOR]

Abstract Dechirp technology for LFM (liner frequency modulation) echo signal will cause sidelobe. The sidelobe of a strong scattering object may mask weak scattering targets nearby. By suppressing the sidelobe in the specified location with a calculated window function, the sidelobe masking can be eliminated. The mainlobe level and the sidelobe level in the specified location are used to construct the objective function. By iterating, we can suppress the sidelobe in the specified location without mainlobe attenuation. The numerical simulations and the actual measurements demonstrate that the proposed method can suppress sidelobe successfully and eliminate the sidelobe masking effectively without mainlobe attenuatio. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we investigate market resiliency as one of the stock market liquidity dimensions. A new methodology for stock resiliency measurement based on Discrete Fourier Transform (DFT) for high-frequency intraday data is introduced. The known disadvantage of DFT is signal leakage. Therefore, the modified formula for resiliency proxy that decreases the signal leakage impact by filtering is utilized. Three alternative window functions are employed: (1) the Hamming window, (2) the Kaiser window, and (3) the SR785 Flat-Top window. Furthermore, there is provided statistical analysis of the results, including its significance and some additional properties. The findings of empirical experiments for real-data from the Warsaw Stock Exchange reveal that the results rather turn out to be robust to the choice of the window filter. Thus, the DFT approach might be considered an auspicious resiliency proxy with an intuitive base. Highlights • Stock market resiliency as one of market liquidity dimensions is investigated. • A new methodology for resiliency estimation is introduced. • Discrete Fourier Transform for high-frequency intraday data is utilized. • A modified formula for resiliency proxy with a window function is yielded. • Real-data analysis of market resiliency on the Polish stock market is provided. [ABSTRACT FROM AUTHOR]

The geological and structural conditions define the radon situation inside a building. While the geological realities can be specified by the content of radium-226 and the ratio of radon-222 emitted from the ground the structural conditions are defined by the tightness of the building envelope. The radon concentration inside has an unsteady character, which is caused by meteorological conditions outside and the air change rate (ACH or ACR), which in turn is influenced by the residents’ behaviour such as venting and heating. For the assessment of the radon exposition, it is necessary to perform measurements for a long time. An approach to reduce this time by eliminating the inhabitants influence on the radon concentration is the radon emission rate, also known as radon entry rate. This variable is based on the measurement of the radon concentration and the parallel determination of the air change rate via a tracer gas method, the result expresses a released activity per time. Due to their noisy character, it is necessary to apply a smoothing algorithm to the input parameters. In addition to mean values, the use of window functions, known from digital signal processing, was analysed. For the verification of the whole calculation procedure, simulations and measurements under defined conditions were used. Furthermore, measurements in an uninhabited house showed proof of the capability of the assessment of the radon potential. First examinations of influencing parameters of the radon emission rate showed a possible dependence on the temperature difference inside and outside the building.

The purpose of this paper was to propose a complete analysis and parameter estimations of a new simplified and highly nonlinear hafnium dioxide memristor model that is appropriate for high-frequency signals. For the simulations; a nonlinear window function previously offered by the author together with a highly nonlinear memristor model was used. This model was tuned according to an experimentally recorded current−voltage relationship of a HfO2 memristor. This study offered an estimation of the optimal model parameters using a least squares algorithm in SIMULINK and a methodology for adjusting the model by varying its parameters overbroad ranges. The optimal values of the memristor model parameters were obtained after minimizing the error between the experimental and simulated current−voltage characteristics. A comparison of the obtained errors between the simulated and experimental current−voltage relationships was made. The error derived by the optimization algorithm was a little bit lower than that obtained by the used methodology. To avoid convergence problems; the step function in the considered model was replaced by a differentiable tangent hyperbolic function. A PSpice library model of the HfO2 memristor based on its mathematical model was created. The considered model was successfully applied and tested in a multilayer memristor neural network with bridge memristor−resistor synapses