Multichannel Case Research Articles

Deep-learning-assisted inverse design of polarization-multiplexed structural color filters with ultrahigh saturation based on all-dielectric metasurface

Although great progress has been made for metasurface-based structural color filters, there are still significant challenges in encoding metasurfaces with complex color images, especially in high saturation or multi-channel cases, where traditional iterative optimization calculations demand substantial computational resources. Here, we proposed a dual-channel multilayered all-dielectric metasurface that can generate structural colors accounting for 224% Standard RGB space, 168% Adobe RGB space and 78% of the 1931 CIE chromaticity space under vertically-polarized incidence. A deep learning-based designing approach is introduced to significantly reduce the computing consumption while maintaining high accuracy. Numerical simulations further demonstrated that the proposed design method is effective for encoding both complementary and independent images with high saturation and wide color gamut. Therefore, the proposed color filters may find potential applications in image display, information encryption and optical anti-counterfeiting.

Modeling and Evaluation of a Dynamic Channel Selection Framework for Multi-Channel Operation in ITS-G5

Many years ago, it seemed inconceivable that our cars could drive autonomously or communicate with each other to form a self-organizing convoy or platoon. By 2023, however, technological advances have taken us to the point where most of these goals will be achieved. In the time of what was initially known as Day 1, single-channel Intelligent Transport System (ITS) devices fully met the requirements for safe communication. The trends show that with the rapid development and the emergence of new, more robust Vehicle-to-Everything (V2X) applications, which require higher bandwidth (collectively called Day 2), the current single-channel medium access method in the available ITS bands will no longer achieve the desired capacities. The main reason is that Day 2 and beyond V2X information dissemination protocols introduce increasing packet sizes and sending frequencies. To complete a resource-friendly and more efficient operation with Day 2 or other advanced V2X services, ITS standards present the Multi-Channel Operation (MCO) constellation as a potential solution. In the case of MCO, we use two or more channels simultaneously, thus preventing the radio medium from saturating its capacity. However, there are still several pending questions about MCO applicability, practical usage, configuration, and deployment, to name a few. The primary purpose of this article is to present a dynamic channel selection framework design and implementation capable of modeling and simulating advanced multi-channel communication use cases. We used this framework to investigate Channel Busy Ratio (CBR) based dynamic channel switching within the Artery/OMNeT++ simulation environment.

New quantum algorithm for visual tracking

Visual tracking, which trains a classifier to distinguish the target from the surrounding environment given an initial sample patch containing the target, plays an important role in computer vision. Yu et al. proposed a quantum algorithm for visual tracking (QVT) [Phys. Rev. A 94, 042311 (2016)] with time complexity OϱZϱZ+ϱX2polylogNϵ based on the framework proposed by Henriques et al. [IEEE Trans. Pattern Anal. Mach. Intell. 7, 583 (2015)], where ϱXZ is the condition number of the data matrix XZ, N is the dimension of the original sample patch, and ϵ is the desired accuracy of the output state. To get a further speedup, we propose a new QVT with time complexity OϱZ1+ϱXpolylogNϵ based on the algorithm of Henriques et al. Our algorithm achieves a quadratic speedup on the condition number ϱX(Z) compared to the algorithm of Yu et al. Also, it shows exponential speedups on N over the classical counterpart when ϱX(Z) and ϵ are OpolylogN. Finally, we extend it to the nonlinear two-dimensional multi-channel case.

Depth-wise Decomposition for Accelerating Separable Convolutions in Efficient Convolutional Neural Networks

Very deep convolutional neural networks (CNNs) have been firmly established as the primary methods for many computer vision tasks. However, most state-of-the-art CNNs are large, which results in high inference latency. Depth-wise separable convolution has been proposed for image recognition tasks on platforms with limited computation power, such as robots and self-driving cars. Any regular deep CNN has a depth-wise separable counterpart, which is faster, but less accurate, when equally trained. In this paper, we propose a novel decomposition approach based on SVD, namely depth-wise decomposition, for converting regular convolutions into depth-wise separable convolutions post-training, while maintaining high accuracy. We show that our approach generalizes to the multi-channel and multi-layer cases, by applying Generalized Singular Value Decomposition (GSVD). We conduct thorough experiments with the ShuffleNet V2 model on a large-scale image recognition dataset: ImageNet. Our approach outperforms the baseline, channel decomposition. Moreover, our approach improves the Top-1 accuracy of ShuffleNet V2 by ∼2%.

Adaptive Fourier Decomposition for Multi-Channel Signal Analysis

Evolved from the conventional Fourier decomposition based on a pre-defined basis, Adaptive Fourier decomposition (AFD) uses adaptive basis to achieve the fast energy convergence. This paper extends the AFD to the multi-channel case, which finds common adaptive basis across all channels. The proposed multi-channel AFD (MAFD) scheme includes the multi-channel core AFD for general signals and the multi-channel unwinding AFD for specific signals that have common inner functions. Owing to the merits of the original AFD, the MAFD can provide sparse joint time-frequency distribution by computing the transient time frequency distribution (TTFD) across channels. Simulations on synthetic and real-world signals demonstrate that the proposed scheme can find and apply the common adaptive basis with desired properties maintained by the AFD, showing high potentials in real-world applications.

A simple alternative to the relativistic Breit\u2013Wigner distribution

First, we discuss the conditions under which the non-relativistic and relativistic types of the Breit–Wigner energy distributions are obtained. Then, upon insisting on the correct normalization of the energy distribution, we introduce a Flatté-like relativistic distribution -denominated as Sill distribution- that (i) contains left-threshold effects, (ii) is properly normalized for any decay width, (iii) can be obtained as an appropriate limit in which the decay width is a constant, (iv) is easily generalized to the multi-channel case (v) as well as to a convoluted form in case of a decay chain and - last but not least - (vi) is simple to deal with. We compare the Sill distribution to spectral functions derived within specific QFT models and show that it fairs well in concrete examples that involve a fit to experimental data for the rho , a_1(1260), and K^*(982) mesons as well as the varDelta (1232) baryon. We also present a study of the f_2(1270) which has more than one possible decay channels. Finally, we discuss the limitations of the Sill distribution using the a_0(980)-a_0(1450) and the K_0^*(700)-K_0^*(1430) resonances as examples.

Jamming and Anti-Jamming Strategies of Mobile Vehicles

Anti-jamming games have become a popular research topic. However, there are not many publications devoted to such games in the case of vehicular ad hoc networks (VANETs). We considered a VANET anti-jamming game on the road using a realistic driving model. Further, we assumed the quadratic power function in both vehicle and jammer utility functions instead of the standard linear term. This makes the game model more realistic. Using mathematical methods, we expressed the Nash equilibrium through the system parameters in single-channel and multi-channel cases. Since the network parameters are usually unknown, we also compared the performance of several reinforcement learning algorithms that iteratively converge to the Nash equilibrium predicted analytically without having any information about the environment in the static and dynamic scenarios.

Universal properties of boundary and interface charges in multichannel one-dimensional models without symmetry constraints

The boundary charge that accumulates at the edge of a one-dimensional single-channel insulator is known to possess the universal property, that its change under a lattice shift towards the edge by one site is given by the sum of the average bulk electronic density and a topologically invariant contribution, restricted to the values $0$ and $-1$ [Phys. Rev. B 101, 165304 (2020)]. This quantized contribution is associated with particle-hole duality, ensures charge conservation and fixes the mod(1) ambiguity appearing in the Modern Theory of Polarization. In the present work we generalize the above-mentioned single-channel results to the multichannel case by employing the technique of boundary Green's functions. We show that the topological invariant associated with the change in boundary charge under a lattice shift in multichannel models can be expressed as a winding number of a certain combination of components of bulk Green's functions as function of the complex frequency, as it encircles the section of the energy axis that corresponds to the occupied part of the spectrum. We observe that this winding number is restricted to values ranging from $-N_c$ to $0$, where $N_c$ is the number of channels (orbitals) per site. Furthermore, we consider translationally invariant one-dimensional multichannel models with an impurity and introduce topological indices which correspond to the quantized charge that accumulates around said impurity. These invariants are again given in terms of winding numbers of combinations of components of bulk Green's functions. Through this construction we provide a rigorous mathematical proof of the so called nearsightedness principle formulated by W. Kohn [Phys. Rev. Lett. 76, 3168 (1996)] for noninteracting multichannel lattice models.

Genesis and fading away of persistent currents in a Corbino disk geometry

The detailed analytical and numerical analysis of the electron spectrum, persistent currents, and their densities for an annulus placed in a constant magnetic field (Corbino disk geometry) is presented. We calculate the current density profiles and study their dependence on the inner and outer radii of the annular. We study evolution of the persistent currents and track their emergence and decay for different limiting cases of such a geometry, starting from a nanodot and ending by a macroscopic circle. Our analytical results for the currents are confirmed by the agreement between the integration of the corresponding current densities and the application of the Byers-Yang formula, when it is applicable. Among other results we find the general expression for the persistent current in a narrow annulus, which in the one channel approximation reproduces the well-known result for quasi-one dimensional mesoscopic metallic ring. Moreover it allows to analyze the multi-channel case of a relatively wide annulus. Our study can be used for more accurate treatment and interpretation of the experimental data with measurements of the persistent currents in different doubly-connected systems.

Yu-Shiba-Rusinov states in real metals

Theoretical descriptions of Yu-Shiba-Rusinov (YSR) states induced by magnetic impurities inside the gap of a superconductor typically rely on a classical spin model or are restricted to spin-1/2 quantum spins. These models fail to account for important aspects of YSR states induced by transition-metal impurities, including the effects of higher quantum spins coupled to several conduction-electron channels, crystal or ligand-field effects, and magnetic anisotropy. We introduce and explore a zero-bandwidth model, which incorporates these aspects, is readily solved numerically, and analytically tractable in several limiting cases. The principal simplification of the model is to neglect Kondo renormalizations of the exchange couplings between impurity spin and conduction electrons. Nevertheless, we find excellent correspondence in those cases, in which we can compare our results to existing numerical-renormalization-group calculations. We apply the model to obtain and understand phase diagrams as a function of pairing strength and magnetic anisotropy as well as subgap excitation spectra. The single-channel case is most relevant for transition-metal impurities embedded into metallic coordination complexes on superconducting substrates, while the multi-channel case models transition-metal adatoms.

A combined method using singular spectrum analysis and instantaneous frequency for the ground-roll filtering

SUMMARY The noise attenuation is a fundamental step in seismic data processing, especially when ground-roll suppression remains a challenge. Rank-reduction methods have become quite popular in recent decades, as they promote significant improvements in the quality of data, highlighting reflections in seismograms. We present a methodology for ground-roll filtering, which combines the application of a recursive-iterative singular spectrum analysis method, in the time domain, as a particular way to decompose seismic data, with the computation of the average instantaneous frequency of the signal components. This combination allows for a precise estimation and filtering of the ground-roll noise. The frequency values are used for determining, in each component, the low-frequency parts associated with the ground roll. For every single component, the ground roll is attenuated by zeroing, and stacking the data components, where the average instantaneous frequency values match the ground-roll bandwidth of frequency. Also, in order to enhance the lateral coherence of the reflectors, we present an extension of the recursive-iterative algorithm for a multichannel case. The multichannel algorithm is applicable on a shot, or common mid-point family of seismic traces, after the normal moveout correction. The numerical results using real data show the effectiveness of the proposed methodology for ground-roll attenuation and for improving the velocity analysis.

Detection of epileptic seizures from compressively sensed EEG signals for wireless body area networks

Wireless body area networks (WBANs) are gaining popularity for tele-monitoring of biomedical signals such as the electroencephalogram (EEG), with diagnosing and monitoring of epileptic seizures being one of the most important applications. Most seizure-detection algorithms cannot be applied directly to the compressed data in WBANs as they require full reconstruction of original EEG signals. In this study, we propose a novel feature for real-time automatic single-channel seizure detection which does not require complete reconstruction of original EEGs. The feature is based on iteratively applying the orthogonal matching pursuit (OMP) algorithm on the compressed EEG data and computing the rate by which the energies of partially reconstructed signals are increased. The feature, i.e. partial energy difference (PED), is then used for classifying seizure and non-seizure states. We also extend this method to the case for multichannel EEG. In multichannel case, the simultaneous OMP (SOMP) with a low number of iterations (1 and 15 iteration) is applied to the compressed data and the difference between the Frobenius norms of partially reconstructed signals is used as a multivariate feature for the classification of seizure and non-seizure states. The proposed features are used to detect seizure intervals in the EEG database provided by the University of Bonn and the CHB-MIT database. The results show that the proposed features can classify seizure epochs from non-seizures even for compression ratios as small as 0.05. The results also show that the proposed single-channel method achieves improvement of up to 4% for the area under the curve (AUC) with significantly less execution time compared to the benchmark matrix determinant (MD) classification approach. The results of applying the proposed multivariate feature to seizure and non-seizure segments of length 5 s from the CHB-MIT database show that it achieves mean AUC values of 0.941, 0.941, and 0.939 with mean execution times of 9.5, 10.7, and 13.1 s for compression ratios of 0.05, 0.1, and 0.2, respectively. Applying a threshold to the PED in a leave-one-out cross-validation (LOO-CV) scenario generates a sensitivity of 0.873,specificity of 0.710, and accuracy of 0.791 at the compression ratio of 0.05. The proposed single- and multichannel features have the potential for deployment in WBANs for the real-time tele-monitoring of epilepsy patients in healthcare applications.

A Superfast Toeplitz Matrix Inversion Method for Single- and Multi-Channel Inverse Filters and Its Application to Room Equalization

This paper derives a superfast Toeplitz matrix inversion method using FFT techniques. The approach casts the non-periodic Toeplitz matrix solution into a periodic framework and uses the Woodbury matrix inverse identity to express the non-periodic solution as a correction to the time-windowed periodic solution. It is shown that the solution can be implemented using FFT techniques that avoid the calculation of a large matrix inverse. The method is implemented for both single- and multi-channel cases and typical computation times and accuracy are reported for the equalization of simulated and measured room impulse responses.

Fully implantable, multi‐channel microstimulator with tracking supply ribbon, multi‐output charge pump and energy recovery

A novel energy-efficient approach dedicated to high-density implantable stimulators such as visual prostheses is presented. Energy efficiency of the approach proposed in this work is achieved through two ideas: the ‘tracking supply ribbon’ technique and ‘reverse charge pumping’. The proposed approach is implemented, in the multi-channel case, in such a way that power efficiency of each stimulation channel is enhanced according to its specific voltage/current condition and independently from other channels. For this purpose, a multi-channel power-efficient charge pump circuit with small integrated capacitors is proposed. Based on the proposed approach, a fully integrated 16-channel stimulation backend for a visual prosthesis was designed and simulated in the transistor level in a standard 0.18-μm triple-well CMOS technology, occupying 1.41 mm2 of silicon area. According to post-layout simulation results, power savings of up to 74% for a single channel and 81.5% for multiple channels are achieved compared to the conventional output stage with a constant supply voltage. Designed for the proposed stimulation backend, the charge pump generates output voltages of 3.48 V, −1.69 V, −3.38 V, and −5.05 V out of a 1.8 V input voltage and exhibits average power efficiency of 92.8% and 86.8% for one- and three-stage circuits, respectively, all in the case of a 100 μA current load. All the aforementioned results are based on post-layout simulation. Moreover, a proof-of-concept prototype was developed using off-the-shelf components in order to demonstrate the operation of the proposed tracking supply ribbon idea.

Room Impulse Response Reshaping and Crosstalk Cancellation Using Convex Optimization

In this article, a new convex formulation for the acoustic channel-equalization problem is proposed and efficient ways for solving it are presented. Both the alternating direction method of multipliers and a proximal algorithm are studied for optimization. Time-domain and frequency-domain constraints are included in an equal way, allowing for simultaneous reverberation reduction and frequency-response equalization. Rather than aiming at full channel equalization, we follow the channel-reshaping paradigm proposed in earlier works and try to push the reverberation tail under the temporal masking limit of the human auditory system, thus making reverberation inaudible for human listeners. While the algorithm is presented for the multiple-input-multiple-output (MIMO) scenario, the single-channel case is included as a special case. Comparisons with methods from the literature for the single- and multi-channel cases show that the new algorithm has faster convergence than the known ones. The proximal algorithm even allows for solving extremely large problems with very low memory demand.

Comparison of intra-wound drainage tubes after cardiac surgery: Blake drains versus Multichannel drains.

Blake and Multichannel drains have been used in our department. Although both are made up of silicone, they differ in structure. We investigated the drainage effects of these two types of drains and the factors related to their occlusion. We enrolled 100 consecutive cases (50 using Blake drains and 50 using Multichannel drains) of cardiovascular surgery performed in our department from July 2017 to April 2018. The formation of thrombi in the groove and tube of the drains was evaluated in each case. The tube portion was checked for the presence of occlusion, and the groove portion was examined for the number and ratio of thrombi formed in the grooves. The clot formation rate in the groove part was slightly higher in the Multichannel cases than in the Blake cases. In addition, analysis within the Multichannel cases revealed that the thrombus formation rate between the catheter lumen and the three grooves (without the catheter lumen) was significantly different, with the highest groove clot formation rate occurring in the catheter lumen. Out of 34 cases of occlusions, there were 26 cases (52%) of Multichannel drains, and only 8 cases (16%) of Blake drains (p < 0.01). A multiple logistic regression analysis revealed that the most important contributory factor in tube obstruction was the drain type. The catheter lumen of the Multichannel drain was more susceptible to thrombus formation than the groove. The tube part of the Multichannel drain was more prone to occlusion than that of the Blake drain.

The global Beta test for hidden periodicities in signals and its extensions to multivariate systems

Background and objectiveThere are many phenomena that lead to changes in the power spectrum of a given signal, and their detection has been a challenge that has received considerable attention over the years. Objective Response Detection (ORD) techniques are a set of tools that perform automated tests for such a task, allowing thus to automatically track changes in the spectrum. The performance of these detectors is affected by the signal-to-noise ratio (SNR) of the recorded signal as well as the length of the available data. The Global F Test (GFT) is a promising detector that can be used to test whether there is a statistically significant difference between the spectrum before and during an event. In fact, this detector has proved useful in the detection of event-related desynchronization/synchronization (ERD/ERS), where only amplitude, but not the phase, changes are locked to the stimulus. In order to improve the statistical power of the GFT (for the same length of recording), multiple channels recorded simultaneously can be included. This concept is called Multivariate Response Detection. The aim of the current work is to extend the GFT to the multivariate (multichannel) case. MethodsFirstly, the single channel normalization of the GFT is presented as a new ORD detector - the global Beta test (GBT). After that, three multivariate extensions of this new test are derived. The critical values used in the detection of spectral changes are obtained by using theoretical distributions, and where this is intractable, by means of Monte Carlo simulations. The probability of detection (PD) of each technique was estimated using simulation and was used in order to compare the detectors performance. A practical example with the electroencephalogram (EEG) from 10 volunteers under intermittent photic stimulation was also provided. ResultsThe statistics under both the null and alternative hypothesis could be obtained for all detectors. Simulated results for PD demonstrate the strong potential of the proposed method and the performances in EEG data are always improved with increasing number of signals. ConclusionIf more than one signal is available, then the multivariate extensions may provide significant benefit compared to the original GFT.

Width and shift of Fano-Feshbach resonances for van der Waals interactions

We revisit the basic properties of Fano-Feshbach resonances in two-body systems with van der Waals tail interactions, such as ultracold neutral atoms. Using a two-channel model and two different methods, we investigate the relationship between the width and shift of the resonances and their dependence on the low-energy parameters of the system. Unlike what was previously believed [Rev. Mod. Phys. 82, 1225 (2010)] for magnetic resonances, we find that the ratio between the width and the shift of a resonance does not depend only on the background scattering length, but also on a closed-channel scattering length. We obtain different limits corresponding to different cases of optical and magnetic resonances. Although the generalisation of the theory to the multi-channel case remains to be done, we found that our two-channel predictions are verified for a specific resonance of lithium-6.

Online multi-channel secondary path modeling in active noise control without auxiliary noise.

Online secondary path modeling is always appealing in active noise control due to the benefit of tracking the variations in the secondary path while exerting noise control simultaneously. However, the auxiliary noise usually utilized in online modeling contributes to the residual noise and deteriorates the noise control performance. This problem is more severe in multi-channel active control systems. Recently, it has been revealed that the secondary path can be identified using the output of the control source directly without injecting any auxiliary noise. In this letter, this strategy is extended to the multi-channel case. The reliability of the secondary path modeling is theoretically proven, and the effectiveness of the proposed multi-channel simultaneous modeling and control system is validated through simulations using measured impulse responses.

Ambisonic Decoding for Compensated Amplitude Panning

Compensated amplitude panning (CAP) is a spatial audio reproduction method for loudspeakers that takes the listener head orientation into account. It can produce stable images in any direction using only two loudspeakers. In its original form, CAP is inherently an object-based method, with each image produced separately. An exact and efficient method is presented here for dynamically decoding a first order Ambisonic encoding, which is equivalent to using CAP to separately reproduce the constituents of the encoding. Both the stereo and multichannel cases are considered.