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There are nonlinear drift memristor models utilizing window functions in the literature. The resistive memories can also be modeled using memristors. If the memristor 's resistance switches from its minimum value to its maximum value or from its maximum value to its minimum value, the transition phenomenon is called resistive or memristive switching. The value of the time required for this transition is especially important for resistive computer memory applications. The switching time is measured by experiments and should be calculatable from the parameters of the memristor model used. In the literature, to the best of our knowledge, the resistive switching times have not been calculated except for the HP memristor model and a piecewise linear memristor model. In this study, the memristive switching times of some of the well-known memristor models using a window function are calculated and found to be infinite. This is not feasible according to the experiments in which a finite memristive switching time is reported. Inspired by these results, a new memristor window function that results in a finite switching time is proposed. The results of this study and the criteria given here can be used to make more realistic memristor models in the future. [ABSTRACT FROM AUTHOR]

This paper proposes two video quality assessment methods based on deep neural network. (i)The first method uses the IQF-CNN (convolution neural network based on image quality features) to build image quality assessment method. The LIVE image database is used to test this method, the experiment show that it is effective. Therefore, this method is extended to the video quality assessment. At first every image frame of video is predicted, next the relationship between different image frames are analyzed by the hysteresis function and different window function to improve the accuracy of video quality assessment. (ii)The second method proposes a video quality assessment method based on convolution neural network (CNN) and gated circular unit network (GRU). First, the spatial features of video frames are extracted using CNN network, next the temporal features of the video frame using GRU network. Finally the extracted temporal and spatial features are analyzed by full connection layer of CNN network to obtain the video quality assessment score. All the above proposed methods are verified on the video databases, and compared with other methods. [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]

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In this paper, we present a memristor model with piecewise window function, which is continuously differentiable and consists of three nonlinear pieces. By introducing two parameters, the shape of this window function can be flexibly adjusted to model different types of memristors. Using this model, one can easily obtain an expression of memristance depending on charge, from which the numerical value of memristance can be readily calculated for any given charge, and eliminate the error occurring in the simulation of some existing window function models. [ABSTRACT FROM AUTHOR]

Abstract: FIR filter design is a kind of constrained multivariable nonlinear function optimization problem. In this paper, we present a novel intelligent method of FIR filter design based on Intelligent Single Particle Optimization improved by priori orientation with an initial window function and convex enable with a dynamic penalty function. By using dynamic penalty function the algorithm is equipped with similar convex nature to generate continuous offspring of legal entity, and we implement a priori directed optimization on the initial particle, which greatly reduces the possibility of particles flying to the area with priori low fitness and speeds up the convergence. In this way, algorithm can search from the optimal spatial which has a very high density of local optimum, then approximate the ideal amplitude-frequency characteristics with fewer iterations. Simulation results illustrated by the case of FIR low-pass filter indicate the effectiveness of the proposed design method. Future works for improving the frequency characteristics of designed FIR filter are proposed in the end. [Copyright &y& Elsevier]

Without noise, Interpolation method for discrete spectrum is an accurate correction method except rounding errors. However, the estimation accuracy can be greatly reduced when a signal corrupted with noise, and even turns Out to be mean- ingless. The paper investigates the influences of windowing and additive White Gaussian Noise on the accuracy of amplitude and phase based on interpolation method. Analytical expressions of the estimator variance for amplitude and phase correction are derived. Simulation results confirm the validity of the presented analysis. We suggest to avoid using interpolation method under the condition that the rectangular window is adopted to correct the phase when the normalization frequency error is small. [ABSTRACT FROM AUTHOR]

A mathematical model of the prototype of memristor, manufactured in 2008 in Hewlett-Packard Labs, is described in the paper. It is shown that the hitherto published approaches to the modeling of boundary conditions need not conform with the requirements for the behavior of a practical circuit element. The described SPICE model of the memristor is thus constructed as an open model, enabling additional modifications of non-linear boundary conditions. Its functionality is illustrated on computer simulations. [ABSTRACT FROM AUTHOR]

Several spectrum correction approaches have been developed, but their improvements deteriorate significantly when they are applied to the correction of the low frequency component (LFC). It is due to that the parameter model underlying the conventional approaches neglects the influence of the negative frequency in the real signal. A new approach is proposed to obtain the LFC parameters from fast Fourier transform (FFT) spectrum lines, which can take into account the contribution from the negative frequency. This explicit approach works only for the rectangular window, and makes use of three spectrum lines around the spectrum main lobe. The proposed approach has been validated by 351 × 180 simulation signal samples. The parameters in these simulated samples distribute widespread. The oscillating cycles covered in record (CiR) range from 1 to 8 by 0. 02, and each CiR case included series samples with the initial phases increased from 0° to 179° by 1°. The maximum error by the proposed approach among 180 phase samples for each CiR is inspected. The simulation results show that so far as the aforementioned widespread parameters range is concerned, the frequency error of the proposed approach is no greater than 0. 000 6Δω, where Δω is the FFT resolution. The errors of the amplitude and phase are not greater than 0. 3% and 0. 3°, respectively. The general trend of error decreases as the CiR increases, but fluctuation indeed exists with the local minimum error aligning with the coherent sampling where the CiR is an integer. [ABSTRACT FROM AUTHOR]