Pair Of Filters Research Articles

Monoblock Antenna-Loaded Filter Pair: Synthesis, Model Extraction, and EM Design

Monoblock Antenna-Loaded Filter Pair: Synthesis, Model Extraction, and EM Design

Dual-polarization carrier-assisted differential detection with asymmetric twin-SSB modulation and simplified receiver structure

Carrier-assisted differential detection (CADD) is a promising solution for high-capacity and cost-sensitive short-reach application scenarios, in which the optical field of a complex-valued double-sideband (CV-DSB) signal is reconstructed without using a local oscillator laser. In this work, we propose a polarization division multiplexed asymmetric twin single-sideband CADD (PDM-ATSSB CADD) scheme to realize the optical field recovery of the PDM CV-DSB signals. The polarization fading is solved by using a pair of optical bandpass filters (OBPFs) to suppress the unwanted other polarized offset carrier and signal, and the dual-polarization optical field is recovered by the CADD receiver. An asymmetric twin-SSB signal is used to relax the sharpness requirement of optical filter edges. We also propose a joint signal-signal beat interference (SSBI) iterative mitigation algorithm, which can effectively mitigate intra- and inter-polarization SSBI. The proposed PDM-ATSSB CADD scheme is validated for 30 Gbaud PDM asymmetric twin-SSB 16-ary quadrature amplitude modulation signals. We illustrate the parameter optimization process for PDM-ATSSB CADD, including optical delay and the number of iterations. The impacts of phase noise and relative intensity noise for laser and polarization impairment on PDM-ATSSB CADD are evaluated through numerical simulation. Compared with the PDM-symmetric-TSSB CADD (PDM-STSSB CADD), the required frequency gap to reach the 7% FEC threshold can be reduced by 1 GHz, and the OSNR sensitivity is improved by about 3 dB. Moreover, two simplified PDM-ATSSB CADD schemes are proposed and discussed, which could be considered hardware-efficient and integrative candidates for metro and inter-data center interconnects.

A general model unifying the adaptive, transient and sustained properties of ON and OFF auditory neural responses.

Sounds are temporal stimuli decomposed into numerous elementary components by the auditory nervous system. For instance, a temporal to spectro-temporal transformation modelling the frequency decomposition performed by the cochlea is a widely adopted first processing step in today's computational models of auditory neural responses. Similarly, increments and decrements in sound intensity (i.e., of the raw waveform itself or of its spectral bands) constitute critical features of the neural code, with high behavioural significance. However, despite the growing attention of the scientific community on auditory OFF responses, their relationship with transient ON, sustained responses and adaptation remains unclear. In this context, we propose a new general model, based on a pair of linear filters, named AdapTrans, that captures both sustained and transient ON and OFF responses into a unifying and easy to expand framework. We demonstrate that filtering audio cochleagrams with AdapTrans permits to accurately render known properties of neural responses measured in different mammal species such as the dependence of OFF responses on the stimulus fall time and on the preceding sound duration. Furthermore, by integrating our framework into gold standard and state-of-the-art machine learning models that predict neural responses from audio stimuli, following a supervised training on a large compilation of electrophysiology datasets (ready-to-deploy PyTorch models and pre-processed datasets shared publicly), we show that AdapTrans systematically improves the prediction accuracy of estimated responses within different cortical areas of the rat and ferret auditory brain. Together, these results motivate the use of our framework for computational and systems neuroscientists willing to increase the plausibility and performances of their models of audition.

Exploring the Effect of Particle Loading Density on Respirable Dust Classification by SEM-EDX

Exposure to respirable coal mine dust (RCMD) still poses health risks to miners. Scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX) is a powerful tool for RCMD characterization because it provides particle-level data, including elemental ratios (via the EDX signals) that can enable classification by inferred mineralogy. However, if the particle loading density (PLD) is high on the analyzed substrate (filter sample), interference between neighboring particles could cause misclassification. To investigate this possibility, a two-part study was conducted. First, the effect of PLD on RCMD classification was isolated by comparing dust particles recovered from the same parent filters under both low- and high-PLD conditions, and a set of modified classification criteria were established to correct for high PLD. Second, the modified criteria were applied to RCMD particles on pairs of filters, with each pair having one filter that was analyzed directly (frequently high PLD) and another filter from which particles were recovered and redeposited prior to analysis (frequently lower PLD). It was expected that application of the modified criteria would improve the agreement between mineralogy distributions for paired filters; however, relatively little change was observed for most pairs. These results suggest that factors other than PLD, including particle agglomeration, can have a substantial effect on the particle EDX data collected during direct-on-filter analysis.

Leveraging statistical-spectral correlations of random metasurfaces for steganography and multi-wavelength cryptography

The ability to tailor the spectral response of photonic devices is paramount to the advancement of a broad range of applications. The vast design space offered by disordered optical media provides enhanced functionality for spectral tailoring while also making it challenging to map the spectral properties of such complex systems to their structural attributes. In this work, we investigate correlations between the configuration statistics of random metasurfaces and their spectral transmissivity in the visible, and leverage those to develop a reduced phase space. In the latter part of the manuscript, we use this reduced phase space to design a pixelated color filter that hides visual data within a preselected cover image for steganography. Furthermore, we design a pair of color filters that can collectively encrypt a given grayscale image in their spectral transmissivities. We envision such devices to create opportunities for the development of compact, next-generation cryptographic systems. More broadly, the results presented in this manuscript provide new, to the best of our knowledge, avenues for optimizing large-scale random metasurfaces to achieve enhanced optical functionalities for a wide variety of applications.

A simple method to construct multivariate dual framelets with high-order vanishing moments

When constructing multivariate framelets, it is often unavoidable to work with matrices of multivariate trigonometric polynomials and complicated matrix decomposition problems. These problems become even harder when good properties such as high-order vanishing moments are required on the framelets. In this paper, we establish a new method for constructing multivariate dual framelets with high-order vanishing moments. The underlying scheme of our algorithm is the famous Mixed Extension Principle that allows us to derive the high-pass filters (or framelet generators) from a given pair of refinable filters with high-order linear-phase moments. Our method only involves two steps: (1) directly constructing the first few pairs of high-pass filters by using the linear-phase moment conditions of the refinement filters; (2) solving a system of linear equations to obtain the rest of the high-pass filters. Both are easy to implement for scientific computation, regardless of what dimension or dilation matrix we work with. Apart from high-order vanishing moments, we will see that if the refinement filters take coefficients from some subfield [Formula: see text] of [Formula: see text] that is closed under complex conjugation, so do the high-pass filters. Furthermore, our algorithm gives the upper bounds for the number of high-pass filters in arbitrary dimensions. At the end of the paper, we will give several illustrative examples, from which we can also see that the support sizes of the high-pass filters are comparable with those of the refinement filters.

SoundCount: Sound Counting from Raw Audio with Dyadic Decomposition Neural Network

In this paper, we study an underexplored, yet important and challenging problem: counting the number of distinct sounds in raw audio characterized by a high degree of polyphonicity. We do so by systematically proposing a novel end-to-end trainable neural network~(which we call DyDecNet, consisting of a dyadic decomposition front-end and backbone network), and quantifying the difficulty level of counting depending on sound polyphonicity. The dyadic decomposition front-end progressively decomposes the raw waveform dyadically along the frequency axis to obtain time-frequency representation in multi-stage, coarse-to-fine manner. Each intermediate waveform convolved by a parent filter is further processed by a pair of child filters that evenly split the parent filter's carried frequency response, with the higher-half child filter encoding the detail and lower-half child filter encoding the approximation. We further introduce an energy gain normalization to normalize sound loudness variance and spectrum overlap, and apply it to each intermediate parent waveform before feeding it to the two child filters. To better quantify sound counting difficulty level, we further design three polyphony-aware metrics: polyphony ratio, max polyphony and mean polyphony. We test DyDecNet on various datasets to show its superiority, and we further show dyadic decomposition network can be used as a general front-end to tackle other acoustic tasks.

EEG stress classification based on Doppler spectral features for ensemble 1D-CNN with LCL activation function

The paper proposes an induced stress classification algorithm that uses features from the Doppler spectrum. In this approach, a reference signal source is used to obtain the quadrature and in-phase components of the EEG signal. The higher frequency components from the in-phase and quadrature are then eliminated using a pair of low-pass filters. The Doppler spectrum was then constructed from which the Doppler frequency features are then estimated. The features that were thus obtained are trained using an ensemble 1D-CNN (one-dimensional Convolutional neural network) which uses two sections of 1D-CNN. The first section 1D-CNN trains the features based on the EEG signal classes namely Stroop test, arithmetic task, and mirror tasks, while the second 1D-CNN section trains the features based on the EEG signal intense classes namely high, low, and medium stress. We also propose a linear-cosine-linear (LCL) activation function for the ensemble 1D-CNN which was derived from the cosine signal. The proposed stress classification scheme was evaluated using the SAM-40 datasets with induced stress classes namely arithmetic task, Stroop color-word test, and mirror image recognition task with stress levels namely high, low, and medium with the evaluation metrics such as precision, F1-score, accuracy, specificity, and recall. The proposed stress classification scheme attains an average accuracy, precision, and recall of 95.25%, 95.22%, and 92.9% when evaluated in 9 classes of EEGs.

Sensor-Fusion-Based Simultaneous Positioning and Vibration Suppression Method for a Three-Degrees-of-Freedom Isolator.

For vibration isolation systems, vibration suppression and platform positioning are both important. Since absolute velocity feedback causes difficulty in achieving positioning while suppressing vibration, an H∞ control strategy based on sensor fusion feedback is proposed in this paper. The signals of inertial and displacement sensors are fused through a pair of complementary filters. Thus, active control based on the fusion signal could concurrently achieve vibration and position control since it is a displacement signal. In addition, the obtained fusion signals have a lower noise level. In this way, simultaneous positioning and vibration suppression can be established using the sensor fusion strategy. On this basis, in order to obtain an optimal H∞ controller, system damping can be maximized by using the performance weight function to attenuate noise; the system bandwidth is determined by the uncertainty weight function, which can avoid the effect of high-frequency modes of the system. The effectiveness of the proposed strategy is verified by comparing it with the conventional absolute velocity feedback strategy on a 3-DOF isolator.

A pair of two-stage Kalman filters to detect and isolate failures in aircraft with redundant actuators

As critically-safe systems, aircraft must be able to adapt if a failure occurs. A fast failure detection may reduce the possibility of loss of control in-flight. Model-based Failure Detection and Isolation Systems (FDIS) have been proposed to identify actuation failures in aircraft, being most of them based on Multiple Models approaches. An additional challenge in FDIS strategies for aircraft is the high level of actuation redundancy. This article proposes to use only a pair of Two-Stage Kalman Filters (TSKF) for detecting and isolating failures. A Feed-Forward Differential (FFD) is introduced to facilitate the fault isolation process, providing further information with low perturbation during flight. The TSKF results are interpreted by a Supervisory Loop, which automatically diagnoses the aircraft for actuation failures. The proposed solution is validated using the Boeing 747 GARTEUR RECOVER Benchmark Simulator. The proposed solution has an overall better response when compared to a multiple-models solution of the literature with an 85% reduction in the computational time.

Congruence filter pairs, equational filter pairs and adjoints

Abstract Filter pairs are a tool for creating and analyzing logics. A filter pair can be seen as a presentation of a logic, given by presenting its lattice of theories as the image of a lattice homomorphism, with certain properties ensuring that the resulting logic is substitution invariant. Every substitution invariant logic arises from a filter pair. Particular classes of logics can be characterized as arising from special classes of filter pairs. We consider so-called congruence filter pairs, i.e. filter pairs for which the domain of the lattice homomorphism is a lattice of congruences for some quasivariety. We show that the class of logics admitting a presentation by such a filter pair is exactly the class of logics having an algebraic semantics. We study the properties of a certain Galois connection coming with such filter pairs. We give criteria for a congruence filter pair to present a logic in some classes of the Leibniz hierarchy by means of this Galois connection, and its interplay with the Leibniz operator.

Thermoluminescence kinetics in beta-irradiated novel ZnGa2O4:Eu3+ phosphor produced via gel combustion synthesis

Eu3+ doped ZnGa2O4 phosphors with varying dopant concentrations were successfully synthesized using the combustion technique. X-ray diffraction analysis confirmed the consistency of both undoped and Eu3+ doped ZnGa2O4 samples with PDF#38–1240 card structure. The investigation of thermoluminescence (TL) characteristics involved studying TL glow curves in Eu3+ doped ZnGa2O4 samples with different dopant concentrations, employing various optical detection filter combinations. Among these, ZnGa2O4: 2%Eu3+ and the IRSL-TL wide blue band (wbb) proved to be the optimal sample and ideal detection filter pairing for identifying TL features. Following preheating experiments, the TL maximum was observed at around 190 °C, with a heating rate of 2 °Cs−1. The dose-response experiment for ZnGa2O4:2%Eu3+ exhibited satisfactory linearity, with a coefficient of b = 0.988 and an R2 value of 0.989 for doses up to 100 Gy. Moreover, for the dose range of 200–500 Gy, a sublinear relationship was maintained, with a coefficient of b = 0.31 and an R2 value of 0.988. Hoogenstraaten's method, along with the initial rise method and the Tm-Tstop experiment, was also employed in conjunction with a glow curve fitting package. This comprehensive approach facilitated the determination of the number of peaks, trap structure, and kinetic parameters within the thermoluminescence glow curve. Glow curve deconvolution using specialized software revealed the presence of five well-isolated and overlapping TL glow peaks, achieving a figure of merit (FOM) value of 1.39.

Normalization by orientation-tuned surround in human V1-V3.

An influential account of neuronal responses in primary visual cortex is the normalized energy model. This model is often implemented as a multi-stage computation. The first stage is linear filtering. The second stage is the extraction of contrast energy, whereby a complex cell computes the squared and summed outputs of a pair of the linear filters in quadrature phase. The third stage is normalization, in which a local population of complex cells mutually inhibit one another. Because the population includes cells tuned to a range of orientations and spatial frequencies, the result is that the responses are effectively normalized by the local stimulus contrast. Here, using evidence from human functional MRI, we show that the classical model fails to account for the relative responses to two classes of stimuli: straight, parallel, band-passed contours (gratings), and curved, band-passed contours (snakes). The snakes elicit fMRI responses that are about twice as large as the gratings, yet a traditional divisive normalization model predicts responses that are about the same. Motivated by these observations and others from the literature, we implement a divisive normalization model in which cells matched in orientation tuning ("tuned normalization") preferentially inhibit each other. We first show that this model accounts for differential responses to these two classes of stimuli. We then show that the model successfully generalizes to other band-pass textures, both in V1 and in extrastriate cortex (V2 and V3). We conclude that even in primary visual cortex, complex features of images such as the degree of heterogeneity, can have large effects on neural responses.

Integrated-optic chromatic dispersion compensator with completely passive operation and wide operational bandwidth

I report on a fiber chromatic dispersion compensator comprising an array of 100 fixed delay lines sandwiched by a pair of arrayed-waveguide grating-type wavelength filters. The requisite delay for the dispersion compensation is allocated to each demultiplexed wavelength component after the first wavelength filter, and the wavelength components are again multiplexed at the second filter. The flexible capability of delay pattern arrangement enables us to realize various fixed dispersion compensation characteristics. I show transmittance and relative delay time characteristics of a multichannel dispersion compensator for short-distance wavelength division multiplexing communication, and its application to dispersion compensation for a pulse amplitude modulation four signal. I also demonstrate the realization of a dispersion slope compensator for a dispersion-shifted fiber with this configuration.

Volumetric Temperature Mapping Using Light-Sheet Microscopy and Upconversion Fluorescence from Micro- and Nano-Rare Earth Composites.

We present a combination of light-sheet excitation and two-dimensional fluorescence intensity ratio (FIR) measurements as a simple and promising technique for three-dimensional temperature mapping. The feasibility of this approach is demonstrated with samples fabricated with sodium yttrium fluoride nanoparticles co-doped with rare-earth ytterbium and erbium ions (NaYF4:Yb3+/Er3+) incorporated into polydimethylsiloxane (PDMS) as a host material. In addition, we also evaluate the technique using lipid-coated NaYF4:Yb3+/Er3+ nanoparticles immersed in agar. The composite materials show upconverted (UC) fluorescence bands when excited by a 980 nm near-infrared laser light-sheet. Using a single CMOS camera and a pair of interferometric optical filters to specifically image the two thermally-coupled bands (at 525 and 550 nm), the two-dimensional FIR and, hence, the temperature map can be readily obtained. The proposed method can take optically sectioned (confocal-like) images with good optical resolution over relatively large samples (up to the millimetric scale) for further 3D temperature reconstruction.

Coarse-to-fine interaction on perceived depth in compound grating.

To encode binocular disparity, the visual system uses a pair of left eye and right eye bandpass filters with either a position or a phase offset between them. Such pairs are considered to exit at multiple scales to encode a wide range of disparity. However, local disparity measurements by bandpass mechanisms can be ambiguous, particularly when the actual disparity is larger than a half-cycle of the preferred spatial frequency of the filter, which often occurs in fine scales. In this study, we investigated whether the visual system uses a coarse-to-fine interaction to resolve this ambiguity at finer scales for depth estimation from disparity. The stimuli were stereo grating patches composed of a target and comparison patterns. The target patterns contained spatial frequencies of 1 and 4 cycles per degree (cpd). The phase disparity of the low-frequency component was 0° (at the horopter), -90° (uncrossed), or 90° (crossed), and that of the high-frequency components was changed independent of the low-frequency disparity, in the range between -90° (uncrossed) and 90° (crossed). The observers' task was to indicate whether the target appeared closer to the comparison pattern, which always shared the disparity with the low-frequency component of the target. Regardless of whether the comparison pattern was a 1-cpd + 4-cpd compound or a 1-cpd simple grating, the perceived depth order of the target and the comparison varied in accordance with the phase disparity of the high-frequency component of the target. This effect occurred not only when the low-frequency component was at the horopter, but also when it contained a large disparity corresponding to one cycle of the high-frequency component (±90°). Our findings suggest a coarse-to-fine interaction in multiscale disparity processing, in which the depth interpretation of the high-frequency changes based on the disparity of the low-frequency component.

Dual-Polarized Duplex Patch Antenna Based on a Multiport Ring Feeding Structure

This letter presents a dual-polarized duplex patch antenna using a multi-port ring feeding circuit. The ring circuit consists of four input ports and four output ports. When one input port of the ring circuit is excited, the four output ports form two pairs of differential ports accordingly. Firstly, a four-port wideband patch antenna is developed using this ring feeding circuit. The four output ports of the ring circuit are directly connected to four metal strips and then coupled to the patch radiator. Once any one of the four antenna ports is excited, wide operating bandwidth covering the base-station band 1710-2690 MHz can be obtained. Secondly, a dual-polarized duplex patch antenna is realized by connecting the four antenna input ports to two pairs of bandpass filters. For different requirements, the center frequencies of the two duplex operating bands can be tuned to desired ones within 1710-2690 MHz using specified filters. For demonstration, a prototype of the dual-polarized duplex antenna operating at 2.0 GHz and 2.6 GHz is implemented. Better than 26 dB measured isolation between all the four ports is realized.

Thermoluminescence behavior of Ce3+ doped lanthanum tri-borate phosphor for dosimetry applications

The combustion method was used to synthesize Ce3+ doped LaB3O6 phosphors in a range of dopant concentrations. Both the un-doped and Ce3+ doped LaB3O6 samples matched the required reference card, according to X-ray diffraction patterns. TL glow curves of Ce3+ doped LaB3O6 samples at various dopant concentrations were examined by employing various optical detection filter combinations to define TL characteristics. LaB3O6:Ce3+ (1%) and IRSL-TL 565 nm were selected as the suitable sample and appropriate detection filter pairing. The TL maximum with a higher intensity was seen during preheating trials (with 2 °Cs−1) at around 270 °C. The experimental results showed feasible linearity (R2 = 0.998 and b = 1.054) between 5 and 1000 Gy for the dose response of LaB3O6:Ce3+ (1%). The short-term fading test was conducted at various time intervals up to a week. The findings showed that the dosimetric peak strength was almost constant for up to 5 days. However, an additional spurious maximum appeared at the higher temperature zone. Each sample showed an abnormal heating rate effect, which can be explained by localized electrons caught in the intermediate excited state, which is capable of radiative transitions via the conduction band. To find the overlapping peak numbers and determine the kinetic parameters of preheated LaB3O6:Ce3+ (1%), various heating rates, TM-Ts, initial rise, and computerized glow curve deconvolution techniques were utilized. The results suggest that LaB3O6:Ce3+ may be an appropriate material for TL dosimetry applications due to its efficient TL characteristics.

$\mathcal{l}_{1}$ Filtering for Positive Takagi–Sugeno Fuzzy Systems via Successive Linear Programming

This paper studies the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {l}_{1}$</tex-math></inline-formula> filtering problem for positive Takagi-Sugeno (T-S) fuzzy systems. A pair of filters are sought to assure stability and positivity of filtering error systems with guaranteed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {l}_{1}$</tex-math></inline-formula> performance indices. For this purpose, a pair of linear co-positive Lyapunov functions that capture the positivity characteristics of filtering error systems are adopted to derive sufficient conditions for the existence of filters, which boils down to the bilinear programming problem. To solve this dilemma, we propose a convex approximation strategy, and thus a sequence of convex surrogates are developed to reasonably replace the non-convex constraints, based on which a successive linear programming algorithm is constructed. Therefore, the filters can be achieved by solving a battery of linear programmings. Finally, the efficiency of the designed filtering scheme was justified by simulation validations.

Transformation of ICEBall to fIREBall for conversion electron spectroscopy

Conversion electron spectroscopy is a valuable tool in nuclear structure studies, but the complex spectra resulting from the high density of levels in the spectra of heavy nuclei make it difficult to extract the most beneficial information from singles measurements. This work reports on the transformation of ICEBall, which was a mini-orange spectrometer that was used in coincidence with various Germanium detector arrays, to the improved fInternal conveRsion Electron Ball (fIREBall) spectrometer for the improved measurements of E0 transitions and conversion electron coefficients. A combination of FreeCAD, COMSOL, and Geant4 simulations were implemented to optimize the geometries for the magnet filters used in the spectrometer to significantly improve the efficiency of electron collection in the energy range of interest 200 keV-1 MeV. The array of six mini-orange Si(Li) detectors are to be replaced with six new, thicker Si(Li) detectors. Experimental tests reported here show a peak improvement in absolute efficiency from 2.8% to 5.3% for the 482 keV K electron line in 207Bi for a single magnet filter and detector pair.