Differential Filter Research Articles

Quantum Functionalities Via Feedback Amplification

Feedback amplification is a key technique for synthesizing various important functionalities, especially in electronic circuits involving op-amps. This paper presents a quantum version of this methodology, where the general phase-preserving quantum amplifier and coherent (i.e., measurement-free) feedback are employed to construct various type of systems having useful functionalities: quantum versions of differentiator, integrator, self-oscillator, and active filters. The class of active filters includes the Butterworth filter, which can be used to enhance the capacity of an optical quantum communication channel, and the non-reciprocal amplifier, which enables measurement of a superconducting qubits system as well as protection of it by separating input from output fields. A particularly detailed investigation is performed on the active phase-cancelling filter for realizing a broadband gravitational-wave detector; that is, the feedback amplification method is used to construct an active filter that compensates the phase delay of the signal and eventually recovers the sensitivity in the high frequency regime.

Transient impulses enhancement based on adaptive multi-scale improved differential filter and its application in rotating machines fault diagnosis

Transient impulses caused by local defects are critical for the fault detection of rotating machines. However, they are extremely weak and overwhelmed in the strong noise and harmonic components, making the transient features are very difficult to be extracted. This paper proposes an adaptive multi-scale improved differential filter (AMIDIF) to enhance the identification of transient impulses for rotating machine fault diagnosis. In this scheme, firstly, the AMIDIF is performed to decompose the measured signal of rotating machine into a series of multi-scale improved differential filter (MIDIF) filtered signals. Subsequently, in view of the MIDIF filtered signals exhibit varying extents of validity in revealing fault features, a weighted reconstruction method using correlation analysis is proposed in which the weighted coefficients are counted and distributed to the corresponding MIDIF filtered signals to highlight the effective MIDIF filtered signals and weaken the invalid ones. Finally, the transient impulse components of rotating machinery are obtained by multiplying the weighted coefficients and the MIDIF filtered signals under different scales. Furthermore, the fault types of rotating machines are inferred from the fault defect frequencies in the envelope spectrum of the transient impulses. Simulation analysis and experimental studies are implemented to verify the performance of the AMIDIF compared with the state-of-the-art methods including spectral kurtosis (SK), multi-scale average combination different morphological filter (ACDIF) and multi-scale morphology gradient product operation (MGPO). The results prove that the AMIDIF has excellent performance in extracting transient features for rotating machines fault diagnosis.

Coarse grained simulations of shock-driven turbulent material mixing

We revisit coarse-grained simulation strategies for turbulent material mixing applications involving shock-driven turbulence in the context of the Radiation Adaptive Grid Eulerian (xRAGE) hydrodynamics and Besnard–Harlow–Rauenzahn (BHR) Reynolds-averaged Navier–Stokes codes, using newly available Low-Mach-Corrected (LMC) xRAGE hydrodynamics. Impact assessments are based on comparisons with a relevant shock-tube experiment for which turbulent mixing and velocity data are available. xRAGE Implicit Large-Eddy Simulation (ILES) and a recently proposed xRAGE-BHR bridging paradigm are tested. Bridging models turbulent stresses dynamically, based on decomposing the full stress into modeled and resolved components, using a differential filter as a secondary filtering operation to define the resolved part, and additionally requiring the resolved stress to approach the full stress with grid resolution refinement to ensure realizability of the bridging-based large-eddy simulation. Much improved scale-resolving with LMC-xRAGE ILES and with dynamic LMC-xRAGE/BHR bridging enables higher simulated mixing and turbulence levels on coarser grids. For the tested planar shock-tube case, the more-accurate models can achieve the same level of accuracy with less resolution than required with the highest-fidelity turbulence simulation models typically used at scale with default xRAGE hydrodynamics; two-levels of grid-coarsening savings can be thus achieved for the mixing prediction in these comparisons: one associated with the more-accurate LMC xRAGE hydrodynamics and an additional one from using the dynamic xRAGE-BHR bridging.

Mathematical Analysis and Improvement of the Maximum Spatial Eigenfilter for Direction of Arrival Estimation

Abstract Maximum spatial eigenfiltering improves the accuracy of maximum likelihood direction-of-arrival estimators for closely-spaced signal sources but may interchangeably attenuate widely-spaced signal sources, producing a severe performance degradation. Although this behavior has been observed experimentally, it still lacks a mathematical explanation. In our previous work, we overcame these limitations using a differential spectrum-based spatial filter but this still caused a small degradation in the DOA estimate. In this paper, we develop a mathematical analysis of how the signal source separation and the Karhunen-Loeve expansion affect the passbands of the maximum spatial eigenfilter. The farther the sources, the less significant is the maximum eigenvalue of the spatial correlation matrix and its corresponding eigenvector. Then, the magnitude response of the maximum spatial eigenfilter no longer approximates the spatial power spectrum and is not guaranteed to place multiple passbands around the signal sources. Consequently, we propose a spatial filter built from the eigenvectors of the entire signal subspace. This filter showed an overall runtime smaller than that of our previous work. It also provides a significant reduction in the threshold signal-to-noise ratio for closely-spaced signal sources and does not hamper the estimation for widely-spaced signal sources.

Correlation method and Kalman filter-based adaptive angle rate estimation for time-varying periodic signals of the attitude and heading reference system

An angle differential estimation method is needed for the attitude and heading reference system (AHRS), which is unavailable to measure the angle rate directly. Differential estimation accuracy is seriously affected by the model error of existing differential filters for time-varying periodic angles provided by the AHRSs. To address this challenge, an adaptive angle rate estimation method based on the Kalman filter and correlation method is proposed. The Kalman filter based on the jerk model is selected to estimate the angle rate. The process noise covariance model of the Kalman filter is established considering amplitude and period fluctuations of the periodic signals. The correlation method is then combined with the Kalman filter to estimate the amplitude and period of the periodic signals, which are utilized to optimize the process noise covariance matrix of the Kalman filter. Compared with traditional differential estimation methods, the proposed method improves the angle rate estimation accuracy by adjusting the parameter of the differential filter according to the model error of the time–varying periodical angle. A simulation is conducted to verify the performance of the proposed method by continuously changing the amplitude and period of the signals. Simulation results show that the proposed method is least affected by model error and achieves the best performance compared with seven other traditional rate estimation methods. Turntable and sea tests also demonstrate the correctness and effectiveness of the proposed angle rate estimation method.

Framework for the Restoration of Capsule Endoscopy Images Using Partial Differential Equations-based Filter

ABSTRACT This study presents a design and experimental results of a novel noise reduction framework for capsule endoscopy (CE) images. CE images exhibit random noise, motion blur, and illumination related degradations. These degradations reduce the efficiency of the computer-aided diagnosis (CAD) system. Restoration process aims to minimize degradations as much as possible; however; measurement of the degradations is a challenge. This study proposes a partial differential equation-based filter for the restoration of CE images. The proposed system performs noise removal while retaining high-frequency components. It measures the performance of the proposed restoration framework based on metrics related to image quality. Visual and statistical results show significant improvement in CE image quality. The proposed approach is capable of noise removal while preserving a low level and a few high-level components leading to better results. Finally, it also presents the performance of a CAD system with and without restoration.

Numerical analysis of Crank–Nicolson method for simplified magnetohydrodynamics with linear time relaxation

AbstractThe Crank–Nicolson (CN) finite element method is examined with a linear time relaxation term in this study. The linear differential filter term is added to simplified magnetohydrodynamics (SMHD) equations for numerical regularization and it introduced SMHD linear time relaxation model (SMHDLTRM). The SMHDLTRM model is discretized by CN method in time and the finite element method in space. The stability and convergency of the method are also conducted. The method is unconditionally stable and convergent under the small time step condition. Additionally, this study summarizes the effectiveness of four methods for SMHD and SMHDLTRM. In previous works SMHD is solved with CN and BE methods and SMHDLTRM is solved with BE method. In this study, the CN solutions of the SMHDLTRM are obtained and compared with the other solutions. All computations are conducted by using FreeFem++.

Fluid-structure interaction simulations with a LES filtering approach in solids4Foam

Abstract The goal of this paper is to test solids4Foam, the fluid-structure interaction (FSI) toolbox developed for foam-extend (a branch of OpenFOAM), and assess its flexibility in handling more complex flows. For this purpose, we consider the interaction of an incompressible fluid described by a Leray model with a hyperelastic structure modeled as a Saint Venant-Kirchho material. We focus on a strongly coupled, partitioned fluid-structure interaction (FSI) solver in a finite volume environment, combined with an arbitrary Lagrangian-Eulerian approach to deal with the motion of the fluid domain. For the implementation of the Leray model, which features a nonlinear differential low-pass filter, we adopt a three-step algorithm called Evolve-Filter-Relax. We validate our approach against numerical data available in the literature for the 3D cross flow past a cantilever beam at Reynolds number 100 and 400.

A 32–42-GHz RTWO-Based Frequency Quadrupler Achieving >37 dBc Harmonic Rejection in 22-nm FD-SOI

In this letter, we propose a 32-42-GHz frequency quadrupler that performs digital logic operations between four phase-shifted differential signals at one-fourth of the output frequency. The four phase-shifted signals are generated via a 10-GHz rotary traveling-wave oscillator (RTWO) and are symmetrically routed to the quadrupler using a CMOS buffered clock tree. The harmonic rejection ratio (HRR) is enhanced by employing a differential LC filter tuned at its output center frequency. The proposed frequency quadrupler is implemented in 22-nm FD-SOI CMOS. At 37 GHz, it produces an output power of -4 dBm with a 10% drain efficiency. It consumes 4 mW from 0.8-V supply and occupies a core area of 0.021 mm2. The worst-case HRR for fundamental, second, third, and fifth harmonics are 41.3, 48.6, 41.3, and 37.3 dBc, respectively.

Aerial camera image focusing method based on out-of-phase differential filtering effect

Aerial camera image focusing method based on out-of-phase differential filtering effect

A Novel Moment of Inertia Identification Strategy for Permanent Magnet Motor System Based on Integral Chain Differentiator and Kalman Filter

In a motor control system, the parameters tuning of speed and position controller depend on the value of the moment of inertia. A new moment of inertia identification scheme for permanent magnet motor system was proposed in this paper. This is an extension of the existing acceleration deceleration methods, which solves the large moment of inertia identification error caused by variable angular acceleration, large calculation error of inertia torque, and large measurement noise in the acceleration process. Based on the fact that the angular acceleration is not constant and the sampling signal is noisy, the integral chain differentiator was used to calculate the instantaneous angular acceleration at any time and suppress the sampling signal noise at the same time. The error function with instantaneous angular acceleration and inertia torque as parameters was designed to estimate the moment of inertia. In order to calculate the inertia torque accurately, viscous friction torque was considered in the calculation of inertia torque, and Kalman filter was used to estimate the total load torque to solve the problem of under rank of motor motion equation. Simulation and experimental results showed that the proposed method could effectively identify the moment of inertia in both noisy and noiseless environments.

Asymmetric plasmonic-semiconductor cavities for angle-adjusted dual-band differential absorption responses

Light absorbers are desirable for wide applications in optoelectronic devices. In this work, we propose and demonstrate a new plasmonic absorber platform, which can support two sharp absorption bands with differential features via tuning the incident angle. The absorber is formed by an asymmetrical metal–semiconductor–metal(MSM) stack intercalated by metal micro-cavities. The maximal absorption for the two peaks respectively reaches 99.8% (λ=0.983μm) and 98.9% (λ=1.187μm). Importantly, the dual-band absorber shows remarkable differential properties when the incident angle is tuned. For instance, the wavelength position is only with a 2 nm fluctuation for the first band in the shorter wavelength range, suggesting a nearly stable state during the angle changes from 0° to 50°. Nevertheless, the wavelength position shifts up to 37.5 nm for the second band in the longer wavelength region, indicating an angle-sensitive absorption. These properties are mainly related to the relaxed resonant fields from the MSM cavities and their different coupling modes to the adjacent metal cavities in this asymmetric structure. These new findings could pave applications for differential optoelectronic manipulations, filters and photo-detection, etc.

Design and Performance of a Toluene-Degrading Differential Biotrickling Filter as an Alternative Research Tool to Column Reactors

AbstractA differential biotrickling filter (DBTF) was developed as a research tool to minimize radial and longitudinal gradients, which hinder analysis in integral (column) reactors. The main desig...

Unsupervised Palm Vein Image Segmentation

In this article the new hybrid algorithm for palm vein image segmentation using convolutional neural network and principal curvatures is proposed. After palm vein image preprocessing vein structure is detected using unsupervised learning approach based on W-Net architecture, that ties together into a single autoencoder two fully convolutional neural network architectures, each simi-lar to the U-Net. Then segmentation results are improved using principal cur-vatures technique. Some vein points with highest maximum principal curva-ture values are selected, and the other vein points are found by moving from starting points along the direction of minimum principal curvature. To obtain the final vein image segmentation the result of intersection of the principal curvatures-based and neural network-based segmentations is taken. The evaluation of the proposed unsupervised image segmentation method based on palm vein recognition results using multilobe differential filters is given. Test results using CASIA multi-spectral palmprint image database show the effectiveness of the proposed segmentation approach.

Position Identification for Robust Myoelectric Control Against Electrode Shift.

The vulnerability to the electrode shift was one of the key barriers to the wide application of pattern recognition-based (PR-based) myoelectric control systems outside the controlled laboratory conditions. To overcome this challenge, a novel framework named position identification (PI) was proposed. In the PI framework, an anchor gesture performed by the user was first analyzed to identify the current electrode position from a pool of potential electrode shift positions. Next, the classifier calibrated by the data of the identified position would be selected for following myoelectric control tasks. The results of the amputee and able-bodied participants both demonstrated that the differential filter combined with majority voting improved the PI accuracy. With only one second contraction of the chosen anchor gesture (hand close), the subsequent PR-based myoelectric control performance was fully restored from eight different electrode shift scenarios, with 1 cm in either or both perpendicular and parallel directions. The classification accuracies with PI framework were not significant before and after the shift ( 0.001). The advantage of restoring performance fully in just one second made it a practical solution to improve the robustness of PR-based myoelectric control systems in a wide range of real-world applications.

Automatic control of working car engine vibrations using multi-stage discrete Fourier transformation

There are questions connected with work of automotive internal combustion engines quality control digitalization. The research goal is formalization of necessary and enough condition of automatic control of such engines’ vibration levels by discrete Fourier transformation digital methods without completing hardware-intensive multiplication operations. During research there are used methods of mathematic and hardware-intensive modeling of digital algorithms of discrete Fourier transformation work and differential filtration on programmed logical integral devices. There are principals of this engine vibrations’ level by digital methods of multi-stage discrete Fourier transformation, which does not require completing algorithmic multiplication operations. There are given formulas of such digital signals’ transformation of differential digital filters by only algebraic addition of timing counts of these signals. The research results have shown and confirmed a possibility of lowering hardware costs with hardware and software realization of digital algorithms of working automotive internal combustion engine vibrations on programmed logical integral devices.

Assessing Synchrophasor Estimates of an Event Captured by a Phasor Measurement Unit

Synchrophasor estimators are nowadays evaluated with the Total Vector Error (TVE) using the synchrophasor representations of the few benchmark signals. This synchrophasor dependence prevents its application to power signals of real events. A new method to obtain the synchrophasor of real signals is proposed in this paper. A finite impulse response (FIR) filter, designed with the nonic O-spline is proposed to obtain phasor estimates asymptotically close to those of an ideal bandpass filter. The phasor estimation accuracy of one or several Phasor Measurement Units (PMUs) can be then assessed using the standard. In addition, it is possible to design two FIR differentiators to obtain frequency and ROCOF estimates close enough to those of ideal differentiator filters, and largely compliant with the standard. This new set of filters opens the way to apply the synchrophasor standard to assess estimates of PMUs of different brands when they process the same signals of a power system event. In this paper, the erratic phasor and frequency estimates produced by a SEL-351 A PMU from a real distributed generation system are assessed to corroborate that the synchrophasor standard can be opened to this new application based on real signals from the field, previously considered as impossible.

ОСОБЛИВОСТІ ВИМІРЮВАННЯ ТА ЕФЕКТИВНОГО ПРИТЛУМЛЕННЯ НАПРУГИ КОНДУКТИВНИХ ЕЛЕКТРОМАГНІТНИХ ЗАВАД ВІД ТРАНЗИСТОРНИХ ПЕРЕТВОРЮВАЧІВ НАПРУГИ

The paper considers voltage converters as sources of conductive electromagnetic interference (EMI). Some features of the standard measurement method of converters EMI are considered and it is shown that it measures only the total level of noise, which can be the same at completely different relations between the differential and common components of EMI. This leads to inefficient use of means reducing the total converter noise to the permitted level, because the different ratio between the above components of this noise requires different means to reduce them. The paper proposes to supplement the standard noise measurement method by two additional measurements at frequencies where the total noise exceeds the permitted level, using during the first measurement the additional RFI common mode filter which effectively reduces only the common noise, and the additional RFI differential mode filter which effectively reduces only the differential noise during the second measurement. It is shown that these two additional measurements make it possible to determine the differential and common components of the total noise. This, in turn, makes it possible to reduce the total noise to the permitted level at the minimal cost. References 6.

Dim and Small Targets Detection in Sequence Images Based on Spatiotemporal Motion Characteristics

In order to effectively enhance the low detection rates of dim and small targets caused by dynamic backgrounds, this paper proposes a detection algorithm for dim and small targets in sequence images based on spatiotemporal motion characteristics. With regard to the spatial domain, this paper proposes an improved anisotropic background filtering algorithm that makes full use of the gradient differences between the target and the background pixels in the eight directions of the spatial domain and selects the mean value of the three directions with the lowest diffusion function in the eight directions as the differential filter to obtain a differential image. Then, the paper proposes a directional energy correlation enhancement algorithm in the time domain. Finally, based on the above preprocessing operations, we construct a dim and small targets detection algorithm in sequence images with local motion characteristics, which achieves target detection by determining the number of occurrences of the target, the number of displacements, and the total cumulative area in these sequential images. Experiments show that the proposed detection algorithm in this paper can effectively improve the detection of dim and small targets in dynamic scenes.

Synthesis of Wideband High-Quality Factor Delay- Tunable Fully Differential All-Pass Filters

In this article, all possible wideband fully differential second-order voltage-mode active all-pass filters (APFs) based on a common-source differential amplifier are systematically derived using two-port network modeling techniques and symbolic math CAD tools. The proposed APF structure is based on the generic two-transistor differential-pair and all possible combinations of the surrounding impedances. In particular, 26 transfer functions and a total of 180 APF circuits, all of which can have a pole quality factor ( $Q$ ) value greater than unity, are found to be possible. Hence, the proposed topology can be used to produce APFs with dispersive delay as well as flat delay for true time delay elements. The operation of some APFs is verified with simulations and a selected circuit with tunable peak delay is designed and fabricated in a 65-nm CMOS process. The implemented filter achieved a maximum peak delay of 88.4 ps at 31 GHz, a constant delay of 11.5 ps over the frequency band 5–20 GHz, and a delay $Q$ -factor ( $Q_{D}$ ) value of 3.74, while consuming 1.74 mW from a 1-V supply voltage. The fabricated circuit occupies an area of $0.11\times 0.348$ mm2 and experimentally demonstrates an APF with the highest $Q$ value of any published second-order APF known to the authors.