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This article proposes an Enhanced Memetic Differential Evolution (EMDE) for designing digital filters which aim at detecting defects of the paper produced during an industrial process. Defect detection is handled by means of two Gabor filters and their design is performed by the EMDE. The EMDE is a novel adaptive evolutionary algorithm which combines the powerful explorative features of Differential Evolution with the exploitative features of three local search algorithms employing different pivot rules and neighborhood generating functions. These local search algorithms are the Hooke Jeeves Algorithm, a Stochastic Local Search, and Simulated Annealing. The local search algorithms are adaptively coordinated by means of a control parameter that measures fitness distribution among individuals of the population and a novel probabilistic scheme. Numerical results confirm that Differential Evolution is an efficient evolutionary framework for the image processing problem under investigation and show that the EMDE performs well. As a matter of fact, the application of the EMDE leads to a design of an efficiently tailored filter. A comparison with various popular metaheuristics proves the effectiveness of the EMDE in terms of convergence speed, stagnation prevention, and capability in detecting solutions having high performance. [ABSTRACT FROM AUTHOR]

This paper studies the dissipative filtering of uncertain singular time-varying delay Markovian jump systems (MJSs) with nonlinear perturbations and generally uncertain transition rates (GUTRs). We focus on the design of a mixed filter, which can include mode-dependent and mode-independent filters in a unified and simple structure. First, a new Lyapunov–Krasovskii functional is proposed through the delay-decomposition approach, and improved Wirtinger-based integral inequalities are used to obtain a sufficient condition to ensure the stochastic admissibility of the considered uncertain nonlinear singular time-varying delay MJSs with dissipative performance. Based on these ingredients, the explicit expression of the desired mixed filter is obtained. Finally, some numerical examples and the filter design of a two-loop circuit network reflect the less conservatism and effectiveness of the method in this article. [ABSTRACT FROM AUTHOR]

In recent years, the finite-difference time-domain (FDTD) method has been used to simulate a wide range of frequency dependent media. The accuracy of these simulations often depends on how accurately the complex dielectric constant is simulated in the sampled time domain used by FDTD. This paper describes the process of modelling the complex dielectric constant as a digital filtering problem and uses Z transforms to convert the frequency domain expression to a sampled time domain expression. Copyright © 1999 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The Laplace operator is a differential operator which is used to detect edges of objects in digital images. This paper presents the properties of the most commonly used third-order 3>3 pixels Laplace contour filters including the difference schemes used to derive them. The authors focused on the mathematical properties of the Laplace filters. The basic reasons of the differences of the properties were studied and indicated using their transfer functions and modified differential equations. The relations between the transfer function for the differential Laplace operator and its difference operators were described and presented graphically. The impact of the corner elements of the masks on the results was discussed. This is a theoretical work. The basic research conducted here refers to a few practical examples which are illustrations of the derived conclusions. We are aware that unambiguous and even categorical final statements as well as indication of areas of the results application always require numerous experiments and frequent dissemination of the results. Therefore, we present only a concise procedure of determination of the mathematical properties of the Laplace contour filters matrices. In the next paper we shall present the spectral characteristic of the fifth order filters of the Laplace type. [ABSTRACT FROM AUTHOR]

• This paper proposes a novel indoor PDR method, which uses wearable devices to collect pedestrian acceleration, gyroscope, geomagnetic and electromyographic signals, and other motion data in real-time. An adaptive Gaussian bilateral filtering (AGBF) algorithm is proposed for preprocessing the collected data. An improved step length estimation (SLE) model is also established based on surface electromyography and acceleration signals. The quaternion method is employed to calculate the heading angle, and the angle increment is acquired by integrating the inertial data, and then the heading information at the next moment. By improving the Unscented KF optimized by the particle filter, the heading angle deviation is corrected, reducing gyroscope drift errors. The current position of indoor pedestrians is estimated based on gait detection, SLE, and heading angle estimation. • The main contributions of this work are listed below:(I) This paper proposes an AGBF algorithm, which uses a numerical filter that adaptively adjusts the standard deviation and adopts a targeted denoising strategy, further enhancing the denoising performance. (II) The gait detection method based on the generalized likelihood ratio multi-threshold detection (GLR-MTD) algorithm can adaptively adjust the threshold and is suitable for pedometers, indoor positioning, and other fields. It has extensive universality and meets the needs of engineering applications. (III) We constructed a novel SLE method for the Linear multi-source information fusion (LM-SIF) model, which can provide accurate SLE for the PDR algorithm. (IV) An improved particle filter-unscented Kalman filter algorithm (IPF-UKF) is proposed to estimate the heading angle error. This algorithm can effectively improve the positioning accuracy of real-time pedestrian inertial navigation. (V) Due to infrastructure and historical data independence, PDR methods based on MEMS-IMU and surface electromyography (SEMG) sensors are very easy to integrate with any application that requires high-precision location services. To solve the problems of severe error accumulation and low accuracy of pedestrian trajectory estimation in traditional Pedestrian Dead Reckoning (PDR) positioning technology, this paper proposes a multi-sensor fusion indoor PDR algorithm. Firstly, a generalized likelihood ratio multi-threshold detection algorithm is employed to detect the gait of pedestrians. Then, a linear multi-source information fusion model is constructed for step length estimation. Next, the quaternion strap-down attitude solution is utilized and coupled with an improved particle filter-unscented Kalman filter algorithm to correct heading angle deviations. Finally, integrate them into the PDR algorithm to estimate the pedestrian's position. The proposed PDR method's relative positioning errors for indoor two-dimensional plane and three-dimensional space walking are 0.36 % and 0.435 %, respectively. Compared to four traditional positioning algorithms, it reduces errors by approximately 0.77 %∼1.18 % and 5.42 %∼11.69 %, respectively. Experimental results indicate that the proposed PDR method effective suppression of error accumulation, achieving more accurate indoor PDR results. [ABSTRACT FROM AUTHOR]

This paper presents efficient and practical implementations of sequential data assimilation methods for the Simplified Parameterizations, primitive‐Equation DYnamics (SPEEDY) Model, a well‐known numerical model, into the data assimilation community for climate prediction. In the SPEEDY model, the time evolution of dynamics is performed via the second‐order Leapfrog integration scheme; this time integrator relies on two steps: the position and the velocity. The computational implementation of SPEEDY blends the time integrator and the spatial discretization of dynamics to accelerate algebraic computations. Thus, there is no access to the right‐hand side function of the ordinary differential equations governing the time evolution of model dynamics. Consequently, the SPEEDY model is often treated as a black box wherein positions and velocities work as inputs and outputs. Since observations in operational data assimilation only match position states, we can exploit augmented vector states to propagate analysis innovations from positions to velocities. For this purpose, we formulate three variants of ensemble‐based filters and perform numerical experiments to assess their accuracies. We consider two scenarios for the experiments: an ideal case wherein positions and velocities can be observed and a more realistic one wherein measurements are only accessible for position states. Besides, we discuss the effects of the ensemble size on the accuracies of our formulations and, even more, the typical case in which velocities are not updated across assimilation steps. The results reveal that all filter formulations' accuracies remain the same in terms of Root‐Mean‐Square‐Error by neglecting observations from velocities (a realistic scenario) even for cases wherein the number of measurements decreases to 6% of model components. Furthermore, for all discussed filter implementations, the propagation of analysis increments from position to velocities improves up to 100% the performance of filter implementations wherein velocities are not updated, a typical operational scenario. [ABSTRACT FROM AUTHOR]

The full-cycle discrete Fourier transform (FCDFT) is commonly used to estimate phasors in numerical relays because of its immunity to harmonics and accurate identification of a decaying dc component (DDC) in a fault current. For fast protection of power systems, it is necessary to speed up the phasor estimation by using a data window below one cycle. The conventional least squares (LS) methods below one cycle approximate the DDC as the first several terms of the Taylor series expansion, which degrades the phasor-estimation accuracy. This paper proposes an LS method that uses Fourier analysis for approximation of the DDC to speed up phasor estimation without accuracy degradation. The phasor-estimation accuracy of the proposed method is investigated for the data-window length in simulations using synthetic data of fault currents containing DDC, harmonics, and measurement noise. The phasor-estimation speed is also investigated with respect to the delay of the antialiasing filter in the numerical relay. The proposed method is compared with the conventional LS and FCDFT methods in simulations using synthetic fault-current data. The feasibility of the proposed method is demonstrated through the phasor estimation of simulated transmission-line faults. [ABSTRACT FROM AUTHOR]

The multiarea Thévenin equivalent (MATE) solution framework is used in this work to combine several subsystems, which are solved using different multiple and non-multiple time-step sizes. In the proposed asynchronous MATE-multirate (A-MATE-multirate) solution, each subsystem is solved with the integration step size that is most adequate for its own internal time constants. This paper relaxes the requirement of previous multirate techniques, in which the solution time-steps of different systems must be multiples or submultiples of each other. To this end, this paper introduces the concept of asynchronous updating, in which each subsystem is updated according to its own internal clock. This updating process is performed in a closed-form solution, with external subsystems represented by their interpolated Thévenin equivalents. Interpolation with future values without using extrapolation is possible in the electromagnetic transients program solution because the history source for future time-steps is calculated at previous time-steps. The exchange of information between subsystems is conditioned using filters to avoid numerical problems during the decimation of the fast subsystems and the interpolation of the slow subsystems. The effectiveness of the proposed methodology is verified with examples using multiple and non-multiple time-step sizes. [ABSTRACT FROM AUTHOR]

This paper deals with join-semilattices whose sections, i.e. principal filters, are pseudocomplemented lattices. The pseudocomplement of a v b in the section [b,1] is denoted by a→b and can be considered as the connective implication in a certain kind of intuitionistic logic. Contrary to the case of Brouwerian semilattices, sections need not be distributive lattices. This essentially allows possible applications in non-classical logics. We present a connection of the semilattices mentioned in the beginning with the so-called non-classical implication semilattices which can be converted into I-algebras having everywhere defined operations. Moreover, we relate our structures to sectionally and relatively residuated semilattices which means that our logical structures are closely connected with substructural logics. We show that I-algebras form a congruence distributive, 3-permutable and weakly regular variety. [ABSTRACT FROM AUTHOR]

The article discusses various reports published within the issue, including one by A. Byrne and colleagues on cryptographic processors and software and another by V. S. Sheeba and E. Elias on two-channel finite impulse response filter banks.

We analyze the propagation properties of the numerical versions of one- and two-dimensional wave equations, semi-discretized in space by finite difference schemes. We focus on high-frequency solutions whose propagation can be described, both at the continuous and at the semi-discrete levels, by micro-local tools. We consider uniform and non-uniform numerical grids as well as constant and variable coefficients. The energy of continuous and semi-discrete high-frequency solutions propagates along bi-characteristic rays, but their dynamics are different in the continuous and the semi-discrete setting, because of the nature of the corresponding Hamiltonians. One of the main objectives of this paper is to illustrate through accurate numerical simulations that, in agreement with micro-local theory, numerical high-frequency solutions can bend in an unexpected manner, as a result of the accumulation of the local effects introduced by the heterogeneity of the numerical grid. These effects are enhanced in the multi-dimensional case where the interaction and combination of such behaviors in the various space directions may produce, for instance, the rodeo effect, i.e., waves that are trapped by the numerical grid in closed loops, without ever getting to the exterior boundary. Our analysis allows to explain all such pathological behaviors. Moreover, the discussion in this paper also contributes to the existing theory about the necessity of filtering high-frequency numerical components when dealing with control and inversion problems for waves, which is based very much on the theory of rays and, in particular, on the fact that they can be observed when reaching the exterior boundary of the domain, a key property that can be lost through numerical discretization. [ABSTRACT FROM AUTHOR]

A neural network (NN) with one hidden layer is implemented to establish a relationship between the resolved-scale flow field and the subgrid-scale (SGS) stress for large eddy simulation (LES) of the Burgers equation. Five sets of input are considered for the neural network by combining the velocity gradient and the filter size. The training datasets are obtained by filtering the direct numerical simulation (DNS) results of the Burgers equation with random forcing function. The number of modes is sufficiently large (N = 65 536) to resolve extremely small scales of motion. In the a priori test, a correlation coefficient over 0.93 is achieved for the SGS stress between the NN models and the filtered DNS data. The results of the a posteriori test reveal that the obtained solutions are stable for all NN models without applying any stabilization techniques. However, not all NN models have a reasonable performance when embedded in the LES code. The applicability of the NN models to the Burgers equation with higher and lower viscosity is also investigated, and it is indicated that the most reliable NN models obtained in this paper can be applied to a set of parameters which are different from those used in training. The results of the SGS models constructed using the neural network are also compared with the existing models, and it is shown that the best obtained NN models outperform the Smagorinsky model and the gradient model, and are comparable to the dynamic Smagorinsky model. However, the NN models have an advantage over the dynamic Smagorinsky model in numerical cost. [ABSTRACT FROM AUTHOR]

The classical bistable stochastic resonance (CBSR) has the disadvantage of output saturation, which limits the enhancement capability for weak signal detection. To break the limitation of output saturation, a novel unsaturated piecewise non-linear bistable stochastic resonance (PNBSR) method is proposed. Because the trichotomous noise exists in practical engineering, the PNBSR under trichotomous noise is explored in this paper. The performance of PNBSR is evaluated by the index, i.e., the mean of M times signal-to-noise ratio increase (MSNRI). The double-peak phenomenon of SR is observed under trichotomous noise. Experiments reveal that the proposed PNBSR method performs best on extracting characteristic components from a strong noise background, compared with the CBSR method and the traditional digital filter. Then, the PNBSR is applied to the fault diagnosis of rolling element bearings. The paper focuses on solving practical engineering problems with mathematical methods. [ABSTRACT FROM AUTHOR]

Active damping is a common way to stabilize the current control of LCL-filtered converters. In this paper, the stable region of −180° phase crossing is first identified within a predefined range of grid impedance and LCL parameter variations. Once the phase of the current control loop is in the identified region, a stabilization control can be attained. Subsequently, digital filters can be adopted to achieve active damping by reshaping the open-loop phase. Various digital filters are selected and benchmarked in this paper. It is confirmed that the all-pass filter has a unity gain and adjustable lagging phase before the Nyquist frequency, thereby being a promising solution to the phase reshaping. Therefore, the all-pass filter is employed to move the phase of the open-loop control (i.e., −180° phase crossing) into the targeted region for active damping. Notably, the current controller and the all-pass filter-based active damping can be separately designed, indicating the easy implementation of the active damping. Experimental tests demonstrate that the proposed method can ensure the system stability over a wide range of parameter variations (e.g., grid impedance changes and LCL-filter parameter drifts) while maintaining fast dynamics with the grid-side current control. [ABSTRACT FROM AUTHOR]

This paper proposes a trajectory prediction method based on graph attention network to accurately predict the trajectories of HDV (Human Drive Vehicles) around the ICV (Intelligent Connected Vehicles) under mixed traffic flow scenario on highways. Firstly, the vehicle trajectory data is filtered and smoothed to construct a trajectory prediction dataset containing map information. Secondly, the vehicle interaction relationship graph is constructed based on the position and behavior of vehicles. The high-dimensional spatial interaction relationship features between the target vehicle and surrounding vehicles are extracted using the graph attention network, which serves as input for the encoder-decoder model. Subsequently, an encoder-decoder model based on GRU (Gate Recurrent Unit) is employed to encode time-series features of vehicle trajectory data and generate future trajectories through decoding. Finally, experimental validation using NGSIM (Next Generation Simulation) datasets demonstrates that our proposed method achieves low displacement error in predicting vehicle trajectories compared to models such as GRU, and CNN-GRU (Convolutional Neural Network-Gate Recurrent Unit). • A trajectory prediction method is proposed to accurately predict the trajectories of HDV (Human Drive Vehicles) around the ICV (Intelligent Connected Vehicles) under mixed traffic flow scenario on highways. • The vehicle trajectory data is filtered and smoothed to construct a trajectory prediction dataset containing map information. • The T-GAT-GRU model is constructed, which can better extract the spatial interaction characteristics between vehicles. [ABSTRACT FROM AUTHOR]

This study proposes a novel filtering method for unbiased minimum variance state estimation. A key challenge in the development of digital twinning and system identification of operational civil infrastructure is the difficulties associated with measurement of the often nonstationary, and stochastic unknown input to the system, e.g. traffic, earthquake, and wind loads. Herein a novel algorithm is presented for an unbiased output-only state estimation for linear state space systems with direct feedthrough. In this paper, the problem of state estimation for discrete time systems with unknown input, where no previous assumption is made regarding the probability distribution of the input, is addressed. In this regard, a two-stage output-only filter is proposed. The unbiasedness of the estimation is demonstrated, and the error covariance propagation over time is derived. It is shown that the unknown input of the system can be subsequently reconstructed via the system matrices, the measured responses, and the estimated state vector. A closed-form solution is provided for the parameters associated with pseudo-inverse in gain calculations to ensure the numerical stability of the filter. Three case studies including simulated and laboratory experiments for verification, validation, and cross comparison of the proposed method are presented. The first case study corresponds to a simulated shear building subjected to two different load time histories, a parametric sinusoidal load, and an earthquake ground acceleration. The second case study shows the results for a simulated experiment on a steel railway bridge subjected to a concentrated load. The third case study corresponds to a laboratory shear building subjected to ground motion and observed through accelerometers. The results of the experiments show a good agreement between the "true response" and the filter state estimation. Moreover, the proposed method is compared against a state-of-the-art algorithm. [ABSTRACT FROM AUTHOR]

High-intensity acoustic waves existing commonly in aeronautical and aerospace vehicles manifest nonlinear propagation behaviors. Large-amplitude vibration and irregular shape of the aerospace vehicles further complicate the acoustic responses. This paper is concerned with numerical analysis of finite-amplitude acoustic responses of complex-shaped vibration objects. The time-dependent effect of the solid boundary position due to the large-amplitude vibration of the objects is considered. A set of first-order differential equations is derived to govern the finite-amplitude acoustic wave. A fourth-order dispersion-relation-preserving finite difference formulation is employed to solve the nonlinear acoustic equations on a fixed Cartesian grid. Acoustic responses of the fluid and the vibration of the complex-shaped object are coupled by considering the compatibility conditions on the fluid-solid interface. A ghost-cell sharp-interface immersed boundary method is utilized to relax the conformity requirement between the computational grid and solid boundary. Numerical filters are employed in the computational procedure to suppress numerical oscillations. The present method is validated through several numerical tests. Numerical analysis of finite-amplitude acoustic responses of a complex-shaped object is performed. The nonlinear effect of a finite-amplitude acoustic wave, the time-dependent effect of solid boundary position, and the coupling effect between them on the propagation behaviors of nonlinear acoustic waves are discussed. [ABSTRACT FROM AUTHOR]

Unwanted dispersive wiggles that arise from the leapfrog numerical scheme have been of interest in weather research and other fluid flow studies. A number of differing approaches have been developed over the last few decades to suppress such wiggles. For example, there are methods that use either smoothing filters or adaptive time-stepping. But, in addition to suppressing the wiggles, smoothing filters suppress the solution profile as well. In order to overcome this problem, in this paper, we construct a computationally efficient numerical scheme that simply eliminates the dispersive wiggles while keeping the solution profile intact. [ABSTRACT FROM AUTHOR]

Using numerical filtering techniques allowing us to reduce noise from sferics, we are able to clearly study a new type of differently structured very low frequency (VLF) radio waves above f = 4 kHz at the ground station of Kannuslehto in northern Finland (KAN, MLAT = 64.4°N, L = 5.5). These emissions are intriguing, since they are detected at frequencies above half the electron gyrofrequency in the equatorial plane (fce) for the L-shell of Kannuslehto (fce ~ 5–6 kHz). They are commonly observed at Kannuslehto, but have also been infrequently reported at other stations, sometimes under different names. Their possible common origin and manner of propagation is still under investigation. This paper unifies the nomenclature by regrouping all these waves detected at frequencies higher than the local equatorial 0.5 fce at the L-shell of observation under the name of VLF bursty-patches. While these waves have different spectral features, they appeared mostly composed of hiss bursts with durations of a few seconds to several minutes. They also show periodic features with varying periodicity and shape. They are sometimes characterized by single bursts covering very large frequency ranges of several kHz. We also give a review of the different characteristics of VLF bursty-patches observed at Kannuslehto, which at the moment, is the station with the highest observation rate. We present recent observations between 2019 and 2021. [ABSTRACT FROM AUTHOR]

Magnetic particle tracking is a recently developed technology that can measure the translation and rotation of a particle in an opaque environment like a turbidity flow and fluidized-bed flow. The trajectory reconstruction usually relies on numerical optimization or filtering, which involve artificial parameters or thresholds. Existing analytical reconstruction algorithms have certain limitations and usually depend on the gradient of the magnetic field, which is not easy to measure accurately in many applications. This paper discusses a new semi-analytical solution and the related reconstruction algorithm. The new method can be used for an arbitrary sensor arrangement. To reduce the measurement uncertainty in practical applications, deep neural network (DNN)-based models are developed to denoise the reconstructed trajectory. Compared to traditional approaches such as wavelet-based filtering, the DNN-based denoisers are more accurate in the position reconstruction. However, they often over-smooth the velocity signal, and a hybrid method that combines the wavelet and DNN model provides a more accurate velocity reconstruction. All the DNN-based and wavelet methods perform well in the orientation reconstruction. [ABSTRACT FROM AUTHOR]

In this paper, the harmonic contribution of the broken rotor bar of an induction machine is investigated using an effective combination of the fast Fourier transform (FFT) and a band stop filter. The winding, spatial, grid fed and fault-based harmonics are investigated. Since the fundamental component is the most powerful component as compared to the other frequencies, it decreases the legibility of spectrum, making logarithmic scale inevitable. It also remains a potential threat of burying the fault representative side band frequencies because of its spectral leakage. In this paper, a band stop Chebyshev filter is used to attenuate the fundamental component, which makes the spectrum clearer and easier to understand even on the linear scale. Its good transition band and low passband ripples make it suitable for attenuating the main supply frequency with low impact on the neighbouring side band frequencies. To study the impact of fault on magnetic flux distribution, simulation is done using finite element method with good number of mesh elements and very small step size. The line current is calculated and frequency spectrum is investigated to segregate the spatial and fault frequencies using the proposed technique. The results are further validated by implementing the algorithm on the data measured in the laboratory environment including the grid fed harmonics. [ABSTRACT FROM AUTHOR]

Purpose: The digital down converter (DDC) is a principal component in modern communication systems. The DDC process traditionally entails quadrature down conversion, bandwidth reducing filters and commensurate sample rate reduction. To avoid group delay, distortion linear phase FIR filters are used in the DDC. The filter performance specifications related to deep stopband attenuation, small in-band ripple and narrow transition bandwidth lead to filters with a large number of coefficients. To reduce the computational workload of the filtering process, filtering is often performed as a two-stage process, the first stage being a down sampling Hoegenauer (or cascade-integrated comb) filter and a reduced sample rate FIR filter. An alternative option is an M-Path polyphase partition of a band cantered FIR filter. Even though IIR filters offer reduced workload to implement a specific filtering task, the authors avoid using them because of their poor group delay characteristics. This paper aims to propose the design of M-path, approximately linear phase IIR filters as an alternative option to the M-path FIR filter. Design/methodology/approach: Two filter designs are presented in the paper. The first approach uses linear phase IIR low pass structure to reduce the filter's coefficient. Whereas the second approach uses multipath polyphase structure to design approximately linear phase IIR filter in DDC. Findings: The authors have compared the performance and workload of the proposed polyphase structured IIR filters with state-of-the-art filter design used in DDC. The proposed design is seen to satisfy tight design specification with a significant reduction in arithmetic operations and required power consumption. Originality/value: The proposed design is an alternate solution to the M-path polyphase FIR filter offering very less number of coefficients in the filter design. Proposed DDC using polyphase structured IIR filter satisfies the requirement of linear phase with the least number of computation cost in comparison with other DDC structure. [ABSTRACT FROM AUTHOR]

This paper reports an original technique for accurately estimating the parameters of human vocal tract filters for vowels in English for speech processing applications such as voice recognition. In this paper, the vocal tract filter design problem is reformulated as a general nonlinear optimization problem and solved using a hybrid Genetic Algorithm (GA). The hybrid GA computes a rough estimate of the global minimum using GA and refines using computationally cheap local search. Issues that are of concern in digital filtering such as achieving stability and overcoming finite precision effects are addressed. The objective function for optimization used in this paper is formulated in terms of poles and zeros of the filters to avoid ill-conditioning and to take advantage of symmetries in the location of poles and zeros. Simulation results indicate that the approach presented in this paper provides a close fit in terms of mean square error between the experimental and designed filters. [ABSTRACT FROM AUTHOR]

When transient electromagnetic investigation methods are carried out in the field, the measured data often contain both the induced polarization (IP) effect and the electromagnetic effect. In order to study the IP effect in the transient electromagnetic response, many researchers first calculate the electromagnetic field which considers the IP effect by replacing traditional resistivity with complex resistivity of the Cole-Cole model in the frequency domain. After the forward modeling calculation of the electromagnetic field in the frequency domain that considers the IP effect, the transient electromagnetic field in time-domain is obtained by a time-frequency transform algorithm. In this paper, the resistivity is directly replaced by the time-variant resistivity expression of the Cole-Cole model by using digital filter algorithms when we simulate the transient electromagnetic fields in time-domain. The calculated result of the Cole-Cole model in time-domain and in frequency-domain are consistent with each other, as observed in the horizontal electric field and the vertical magnetic field comparisons, which indicates the correctness of the numerical computation method adopted in this paper. The research presented herein allows us to observe the influence of the IP effect on transient electromagnetic field as well as study the mechanisms of IP directly. [ABSTRACT FROM AUTHOR]

Highlights • The problem of extended dissipativity analysis of digital filters with time delay and Markovian jumping parameters is addressed. • A very general form of nonlinearity functions, which can include the existing nonlinearity function as special cases, is proposed. • By employing the generalized reciprocally convex combination inequality approach, a sufficient condition, under which the underlying system is stochastically stable and satisfies the extended dissipativity, is established. • The stability criterion presented in this paper depends not only on time delay and jumping modes, but also on both the lower and upper bounds of the nonlinearity function, which leads to less conservative results than those existing ones. Abstract This paper considers the problem of extended dissipativity analysis for digital filters, which simultaneously contain time delay and Markovian jumping parameters. First, we put forward a very general form of nonlinearity functions, which can cover the existing nonlinearity functions as special cases. Second, by employing the generalized reciprocally convex combination inequality approach, a sufficient condition is proposed, under which the underlying system is stochastically stable and satisfies the extended dissipativity. Finally, numerical examples are provided to illustrate the advantages and effectiveness of the proposed scheme in this paper. [ABSTRACT FROM AUTHOR]

• A macroscale model is developed to study electrostatic particle filtration. • Multi-layering is proposed as a means of protecting the bipolarly charged fibers. • Unipolar and bipolar charging are considered to lower the pressure drop. • Placing the unipolar layer upstream of the bipolar layer extends filter's life. The deposition of neutral and charged particles inside an electrostatically charged filter can affect its performance by decreasing its ability to capture additional particles and by increasing its pressure drop. The particle-loaded behavior of a composite filter comprised of three fibrous layers is studied in this paper using a macroscale simulation approach. Each of these fibrous layers were assumed to have fibers with the same amount of charge but different charge polarities of only unipolar positive, only unipolar negative, or only bipolar. The charged layers were stacked on top of one another in three different configurations with respect to the flow direction and their filtration efficiency and pressure drop were compared during particle loading with neutralized particles (having the Boltzmann equilibrium charge distribution), singly-charged particles, and neutral particles. Our simulations revealed that placing the bipolarly-charged layer downstream of the unipolarly charged layers helps to lower the negative impact of particle deposition on pressure drop and filtration efficiency of the resulting composite filter. This study introduces a design tool which can be used to optimize the configuration of a composite filter for enhanced particle capture efficiency and reduced pressure drop increase. [ABSTRACT FROM AUTHOR]

• Novel use of photon Doppler velocimeter for soil penetration testing. • PDV incorporated into vertical ballistic range to capture depth-dependent behavior. • High fidelity velocity and force time history in support of modeling. • Produces high fidelity velocity measurement without differentiation or integration. • Advantages, limitations, and details of implementation thoroughly described. This paper presents details for using a photon Doppler velocimeter (PDV) to produce high fidelity velocity penetration data from vertical penetration into granular soil targets. The PDV theory used for collecting data is presented, along with details relevant to soil penetration testing. Experimental aspects related to specific equipment used, measurement configurations implemented, power losses, and probe alignment are presented in order to facilitate replication. The PDV equipment were mounted on a vertical gas gun and used to measure conical and blunt nose rod projectile velocities in penetration into loosely packed and densely packed soil targets. An in-depth discussion of data smoothing and filtering, data sampling and repeatability is presented. Penetration tests in several soil targets are used to reveal important phenomenology of penetration in granular media. The roles of soil target bulk density and pore saturation are investigated in terms of Poncelet drag and bearing resistance parameters. It is shown that bulk density plays a major role in penetration resistance while saturation has a secondary effect. The Poncelet drag coefficient was found to be projectile nose shape dependent. The drag coefficient was as high as 2.0 in penetration of blunt nose projectiles in densely packed sand, while a conical nose reduced the drag coefficient to 1.4. Saturation reduced the drag coefficient by 32 % and 28 % in densely packed and loosely packed soil targets, respectively. [ABSTRACT FROM AUTHOR]

Fault-tolerant digital filters are widely expected for use in modern electronic systems. In this paper, a structure evolution based optimization algorithm (SEOA) for designing an low-pass IIR digital filter is proposed. The filter structure is designed to alleviate the impact of concurrent permanent multiplier failures. A IIR digital filter structure is created by a new mechanism proposed in this paper, which provides not only structural validation and diversity but also a specific structure generation. Genetic algorithm (GA) is redesigned to integrate the mechanism for ensuring that structures are evolved validly and efficiently. In the improved GA, structures with different sizes are crossed by a single point way, which expands the solution space of structures. Desirable structures can be created by adjusting structural parameters, such as the structure size or the connection type. Simulation results show that filter performance is greatly affected by the concurrent short and open circuit faults of multipliers. Compared with the classic IIR digital filter implementations, SEOA improves the fault tolerance of the filter. [ABSTRACT FROM AUTHOR]

A low complexity, low delay reconfigurable digital filter structure for hearing aids is proposed in this paper. The main objective is to match a given human audiogram, with minimum error. The high computational complexity in the conventional uniform and non-uniform filter bank techniques, probes to shift the design paradigm towards variable filter structure. In this paper, Farrow structure based design is used to realize an arbitrary sample rate converter, making use of a differentiator based model, by which the bandwidth can be continuously varied. The proposed design also considers the importance of the power, area, and” delay in such a critical scenario. Exhaustive comparisons are performed with the existing literature on audiogram matching, and our design is very competitive when compared to the designs in the literature, not only with respect to the matching error but also with respect to area, power dissipation, and hardware complexity. [ABSTRACT FROM AUTHOR]

Widely linear (WL) receivers have the capability to perform single antenna interference cancellation (SAIC) of one rectilinear (R) or quasi-rectilinear (QR) co-channel interference (CCI), a function which is operational in global system for mobile communications (GSM) handsets in particular. Moreover, SAIC technology for QR signals is still required for voice services over adaptive multiuser channels on one slot (VAMOS) standard, a recent evolution of both GSM and enhanced data rates for GSM evolution (EDGE) standards, to mitigate legacy GSM CCI in particular. It is also required for filter bank multicarrier offset quadrature amplitude modulation (FBMC-OQAM) networks, which are candidate for 5G mobile networks, to mitigate intercarrier interference at reception for frequency selective propagation channels in particular. In this context, the purpose of this paper is twofold. The first one is to get more insights into the existing SAIC technology, and its extension to multiple antenna called multiple antenna interference cancellation (MAIC), by showing analytically that, contrary to what is accepted as true in the literature, SAIC/MAIC implemented from standard WL filtering may be less efficient for QR signals than for R ones. From this result, the second purpose of the paper is to propose and to analyze, forQRsignals and frequency selective fading channels, an SAIC/MAIC enhancement based on a three-input WL frequency shift receiver, making QR signals always almost equivalent to R ones for WL filtering in the presence of CCI. The results of the paper, completely new, may contribute to develop elsewhere new powerful WL receivers for QR signals and for both VAMOS and FBMC-OQAM networks in particular. [ABSTRACT FROM AUTHOR]

Most existing phasor measurement units (PMUs) are noncausal PMUs and they compensate for the group delay in PMU applications by shifting time stamps, which may result in high latency that will impair performance of PMU applications. This paper presents causal PMUs to reduce the group delay caused latency without shifting time stamps, and studies the impact of causality on performance of PMU algorithms. The paper first analyzes how causal and noncausal PMUs compensate for the group delay caused by digital filters and it is found that causal PMUs normally reduce latency by the group delay, whereas noncausal PMU will not. Then, the impact of causality on performance of PMU algorithms is investigated and analyzed by using the Hydro Quebec Research Institute (IREQ) PMU model and the IEEE PMU model. Finally, the simulation results carried out on two test systems highlight the difference between the causal method and the noncausal method under fault conditions in realistic multimachine setups. [ABSTRACT FROM AUTHOR]

In many applications, sensors that map the positions of objects in unknown environments are installed on dynamic platforms. As measurements are relative to the observer's sensors, scene mapping requires accurate knowledge of the observer state. However, in practice, observer reports are subject to positioning errors. Simultaneous localization and mapping addresses the joint estimation problem of observer localization and scene mapping. State-of-the-art approaches typically use visual or optical sensors and therefore rely on static beacons in the environment to anchor the observer estimate. However, many applications involving sensors that are not conventionally used for Simultaneous Localization and Mapping (SLAM) are affected by highly dynamic scenes, such that the static world assumption is invalid. This paper proposes a novel approach for dynamic scenes, called GEneralized Motion (GEM) SLAM. Based on probability hypothesis density filters, the proposed approach probabilistically anchors the observer state by fusing observer information inferred from the scene with reports of the observer motion. This paper derives the general, theoretical framework for GEM-SLAM, and shows that it generalizes existing Probability Hypothesis Density (PHD)-based SLAM algorithms. Simulations for a model-specific realization using range-bearing sensors and multiple moving objects highlight that GEM-SLAM achieves significant improvements over three benchmark algorithms. [ABSTRACT FROM AUTHOR]

The chord-based measurement system has been used for a long time in the measurement of track irregularity, however, the error theory is seldom studied. As a typical case, the mid-chord offset system (MCO-system) is selected in this paper to study the error propagation of chord-based systems. The measurement model and restoration model are established to describe the measurement and restoration process of the MCO-system. To evaluate the accumulation of error, the Error Amplification Factor (EAF) is defined. The regularities of error accumulation are analyzed in the distance domain and the wavelength domain. Furthermore, an error propagation formula of different wavelengths is proposed. High frequency sampling is introduced to improve the performance of the MCO-system, where a least square model is established to handle the redundant measured data, and it can be theoretically proven that the influence of measuring errors can be reduced to zero if the sampling frequency approaches infinity. The error theory given in this paper is useful for designing devices based on the MCO-system and the error of different wavelengths can be accurately controlled. As an application, field measurement is carried out to verify the feasibility and correctness of the models by comparison with the restoration method using a digital inverse filter. [ABSTRACT FROM AUTHOR]

Servo-hydraulic actuators exhibit frequency-dependent variations of amplitude and delay during real-time hybrid simulation (RTHS). Effective compensation techniques to overcome these variations is a crucial component for the successful implementation of RTHS. Most of the existing compensation techniques have demonstrated effective performance under excitations with relatively low frequency bandwidth. To further advance the servo-hydraulic compensation for broader frequency bandwidth, this paper presents the design and performance evaluation of an optimal discrete-time model-based feedforward controller under inputs with broader frequency bandwidth as high as 0–30 Hz. As a compensation technique has not been fully explored in RTHS, the model-based design of discrete-time domain compensation techniques introduces the new technical challenge of inverting nonminimum phase systems. This paper identifies this new challenge by providing detailed supporting derivation, and explains the use of a digital filtering technique—a finite impulse response (FIR) filter—to address this new challenge, and the development process of the proposed FIR compensator using different optimization schemes. Furthermore, this paper demonstrates the compensation performance of the proposed FIR compensator, both numerically and experimentally, under reference inputs with various bandwidths, including bandlimited white noises with frequency bandwidth as high as 0–30 Hz. For comparison purposes, several existing feedforward compensation techniques are also implemented and compared with the proposed FIR compensator. Based on this study, it is found that the proposed FIR compensator technique not only provides excellent compensation performance under various bandwidths, but also offers great flexibility in its formulation by varying the model order with desired compensation performance and computational demands. [ABSTRACT FROM AUTHOR]

Recently, we discussed the concept of direct synthesis technique (DST), in which real-coefficient filtering polynomials containing all information of the filters to be synthesized are derived directly for realization, and they could find applications in the design of lumped-element LC filters, active RC filters, and infinite impulse response digital filters. In this paper, another DST for complex general Chebyshev bandpass filters is discussed, which is based on a complex mapping relation and featured by complex-coefficient filtering polynomials. It is called as complex DST in this paper. Compared with real-coefficient filtering polynomials whose polarities are determined by the number of their zeros at zero frequency, the polarities of complex-coefficient filtering polynomials can be easily changed by multiplying imaginary unit j. Such advantage might make their realization more flexible. The analysis shows that conventional coupling matrix could be considered as narrow-band approximation of network matrix derived by complex DST in the normalized frequency domain. In order to demonstrate the validity of complex DST in this paper, it is applied in the design of classic parallel-coupled microstrip bandpass filters. Compared with conventional synthesis techniques, complex DST could find out better dimensions and provide more choices for realization and synthesize both even-order and odd-order parallel-coupled microstrip bandpass filters. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to design and implement minimum multiplier, low latency structures of a comb filter. Multipliers are the most area and power consuming elements; therefore, it is desirable to realize a filter with minimum number of multipliers. In this paper, design of comb filters based on lattice wave digital filters (LWDF) structure is proposed to minimize the number of multipliers. The fundamental processing unit employed in LWDF requires only one multiplier. These lattice wave digital comb filters (LWDCFs) are realized using Richards' and transformed first-order and second-order all-pass sections. The resulting structural realizations of LWDCFs exhibit properties such as low coefficient sensitivity, high dynamic range, high overflow level, and low round-off noise. Multiplier coefficients of the proposed structures are implemented with canonic signed digit code (CSDC) technique using shift and add operations leading to multiplierless implementation. This contributes in reduction of number of addition levels which reduces the latency of the critical loop. A field programmable gate array (FPGA) platform is used for evaluation and testing of the proposed LWDCFs to acquire advantages of the parallelism, low cost, and low power consumption. The implementation of the proposed LWDCFs is accomplished on Xilinx Spartan-6 and Virtex-6 FPGA devices. By means of examples, it is shown that the implementations of the proposed LWDCFs attain high maximum sampling frequency, reduced hardware, and low power dissipation compared with the existing comb filter structures. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper is an extension of our paper I-cluster points of filters [8]. In this paper, we have discussed the relationship between I-cluster points of filters and cluster points of nets and estabilished their equivalence.We have also estabilished the equivalence of I-cluster points of filters and nets. [ABSTRACT FROM AUTHOR]

In this paper, we have introduced the concept of I-cluster point of a filter on a topological space and studied its various properties. We have proved the necessary condition for a filter to have an I-cluster point. Most of the work in this paper is inspired from [2] and [23]. [ABSTRACT FROM AUTHOR]

In the middle and later stages of shale gas production, the output declines and the pressure of the gas well decreases. In order to ensure smooth transmission of the product gas, the gas compressor is needed to boost production. Because the shale gas has more particulate impurities than conventional gas, if the impurities are not separation incompletely and go into the downstream, it will cause compressor damage even shut down, which will affect the shale gas production and gathering process, causing huge economic losses. As the last guarantee before shale gas entering the supercharger, the separation efficiency of filter separator is very important. But there are few studies on separation efficiency of horizontal filter separator by numerical calculation method. In this paper, FLUENT software is used for numerical simulation of the horizontal filter separator, and the flow field in the equipment is researched and analyzed. The calculation results show that the filter barrel of horizontal separator can effectively separate solid and liquid particles/ impurities. The separation efficiency is high when the liquid particle size is larger than 60μm and the solid particle size is larger than 30 μm, The overall separation efficiency can reach more than 96% . This method can effectively protect the the compressor lever, optimize the shale gas gathering and transportation technology, and ensure the safe operation of shale gas field. [ABSTRACT FROM AUTHOR]

The power ripple in the input filter is normally ignored in the conventional model predictive control scheme (MPC) of an AC/DC matrix converter under imbalanced grid voltage conditions. Unfortunately, this power ripple causes output power and current ripples. Some methods compensate this power ripple to obtain a ripple-free output current. However, these methods are generally complicated due to the increased computational and control burden or the use of a digital filter to estimate the power ripple. Moreover, the compensation of power ripple results in current distortion on the grid side, which has yet to be fully addressed. This paper presents an improved MPC scheme to simultaneously compensate input filter power ripple and reduce grid current distortion under imbalanced grid voltage conditions. The power ripple is calculated based on the grid voltage and its 90 electrical degrees delay signal, which makes the implementation simple without grid voltage components extraction or digital filter design. Furthermore, a closed-loop current controller is proposed to reduce the harmonic distortion of the grid current. The feasibility of the proposed MPC scheme is confirmed by both simulation and experimental results. [ABSTRACT FROM AUTHOR]

The artificial bee colony algorithm (ABC), as one of the excellent intelligent optimization technologies, has presented very good optimization performance for many complex problems due to its simplicity and easiness of implementation. However, ABC has a very good performance at exploration relatively, but for some complex problems it still results in slower convergent speed and lower convergent accuracy in the later stage of algorithms. Meanwhile, ABC has relatively poor performance at exploitation. To overcome these drawbacks further, the enhancing ABC algorithm using refraction principle is proposed (EABC-RP) in this paper. In EABC-RP, on the one hand, in order to enhance its exploration further, the unified opposition-based learning (UOBL) based on refraction principle is employed to generate refraction solutions (new food sources) for employed bees, which helps to increase population diversity and guide search direction close to the global optimal solution. On the other hand, for exploitation, when ABC has fallen into the local optimal solution, the UOBL based on refraction principle is employed for mutation to increase the probability of jumping out of the local optimal solution for scout bees. A lot of experiments are conducted on 23 benchmark functions to verify the effectiveness of EABC-RP. The experimental results show that EABC-RP achieves higher solution accuracy and faster convergent speed in most cases and outperforms other ABC variants. In addition, EABC-RP is used to optimize finite impulse response (FIR) low-pass digital filter which obtains the better filtering performance, which validates the effectiveness of the EABC-RP algorithm further. [ABSTRACT FROM AUTHOR]

• A supervised filter feature selection method for mixed data is introduced • Spectral analysis and Information-theory based feature selection was applied • Relevant and non-redundant features are selected • An evaluation of the proposed method on 40 public datasets was performed • A comprehensive comparison against state-of-the-art methods was made Spectral analysis and Information-theory are two powerful and successful frameworks for feature selection in supervised classification problems. However, most of the methods developed under these frameworks have been introduced for handling exclusively numerical or non- numerical data. In this paper, we propose a supervised filter feature selection method that combines Spectral Feature Selection and Information-theory based redundancy analysis for selecting relevant and non-redundant features in supervised mixed datasets; i.e., datasets where the objects are described simultaneously by both, numerical and non-numerical features. To demonstrate the effectiveness of our proposed supervised filter feature selection method, we conducted several experiments on 40 public real-world datasets. Additionally, we compare our method against relevant state-of-the-art supervised filter methods for numerical, non-numerical, and mixed data. From this comparison, our method, in general, obtains better results than the results obtained by the other evaluated filter feature selection methods. [ABSTRACT FROM AUTHOR]