Amplitude Estimation Research Articles

Fast Displacement Estimation of Multiple Close Targets with MIMO Radar and MUSICAPES Method

Interferometric radar is a hot research topic in manmade target displacement measuring applications, as it features high precision, a large operation range, and a remote multiple point measuring ability. Most one-dimensional interferometric radars use single-input single-output (SISO) radar architecture to achieve a high repetition measuring rate of more than 200 Hz; however, it cannot resolve multiple targets with the same radial range but different azimuth angles. This paper presents a multiple-input multiple-output (MIMO) radar that adopts a limited number of antennas (usually tens) to simultaneously improve azimuth resolution and achieve a high repetition measuring rate. A MUSICAPES algorithm is proposed, which is cascades the multiple signal classification (MUSIC) algorithm and the amplitude and phase estimation (APES) filter. The MUSIC algorithm is used to further improve the angular resolution of the small array. The APES is used to precisely recover the phases of the multiple close targets by suppressing their mutual interferences. Simulations and experiments with a millimeter-wave radar validate the performance of the proposed method.

Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders?

Bipolar disorder (BD) is characterized by recurrent mood episodes. It is increasingly suggested that disturbances in sleep–wake cycles and/or circadian rhythms could represent valuable predictors of recurrence, but few studies have addressed this question. Euthymic individuals with BD (n = 69) undertook 3 weeks of actigraphy recording and were then followed up for a median duration of 3.5 years. Principal component analyses were used to identify core dimensions of sleep quantity/variability and circadian rhythmicity. Associations between clinical variables and actigraphy dimensions and time to first recurrence were explored using survival analyses, and then using area under the curve (AUC) analyses (early vs. late recurrence). Most participants (64%) experienced a recurrence during follow-up (median survival time: 18 months). After adjusting for potential confounding factors, an actigraphy dimension comprising amplitude and variability/stability of circadian rhythms was a significant predictor of time to recurrence (p = 0.009). The AUC for correct classification of early vs. late recurrence subgroups was only 0.64 for clinical predictors, but combining these variables with objectively measured intra-day variability improved the AUC to 0.82 (p = 0.04). Actigraphy estimates of circadian rhythms, particularly variability/stability and amplitude, may represent valid predictive markers of future BD recurrences and could be putative targets for future psychosocial interventions.

RSS/TDoA-Based Source Localization in Microwave UWB Sensors Networks Using Two Anchor Nodes.

The manuscript presents an algorithm for the optimal estimation of the amplitude and propagation delay time of an ultra-wideband radio signal, in systems for the passive location of fixed targets based on the hybrid RSS/TDoA method in two-dimensional space with two base stations. The optimal estimate is based on the Bayesian strategy of maximum a posteriori probability density, taking into account a priori data on the statistical properties of the Line of Sight radio channel during Gaussian monocycle propagation. The Bayesian Cramer–Rao lower bound (BCRLB) of the delay time and the amplitude estimates for a time-discrete signal are calculated, and the resulting parameter estimate is compared with BCRLB. An algorithm has been developed for optimal estimation of distances from the radiation source to base stations, based on the results of the measurements of the amplitude and the propagation delay time of the UWB radio signal. The calculation of the statistical characteristics of the obtained estimate is carried out, and the functional dependence of the characteristics on various parameters is analyzed.

Deconvolution filter for parameter estimation of composite stress wave propagating in the wooden cylindrical structure

Through-transmission using the embedded waveguide technique in the cross-section plane of cylindrical structure produces radial and Rayleigh modes. These two modes propagate in the heart and shell regions of the plane, allowing a comprehensive characterization of the material. The significant spatial difference generates a distinct temporal separation between the two modes for large cylindrical structures, allowing direct mode characterization. For cylindrical structures with smaller diameters, the pronounced multi-path interference produces an erroneous energy response that hinders the accurate mode characterization. In this so-called multiple-input-single-output (MISO) system, the arrival time and amplitude estimations are an underdetermined problem. This work presents a novel decomposition filter design consisting of three steps. (1) Gabor’s wavelet transforms the stress wave signal in the time-frequency domain; (2) The approximation of the inverse point-spread-function (PSF) response via a series of frequency polynomials generates a set of optimal coefficients; (3) Derive the inverse deconvolution kernel via the dual derivative operator from the obtained optimal coefficients in step 2. This presentation will demonstrate the algorithmic formulation with numerical and empirical validations. Its broader impact will enhance the parametric estimation of the diagnostic stress wave for material characterization.

Receptivity of crossflow instability to discrete roughness amplitude and location

The effect of discrete roughness elements on the development and breakdown of stationary crossflow instability on a swept wing is explored. Receptivity to various element heights and chordwise locations is explored using a combination of experimental and theoretical tools. Forcing configurations, determined based on linear stability predictions, are manufactured and applied on the wing in a low turbulence facility. Measurements are performed using infrared thermography, quantifying the transition front location, and planar particle image velocimetry, providing a reconstruction of stationary crossflow instabilities and their associated growth. Measurements are corroborated with simulations based on nonlinear parabolised stability equations. Results confirm the efficacy of discrete roughness elements in introducing and conditioning stationary crossflow instabilities. Primary instability amplitudes and resulting laminar-turbulent transition location are found to strongly depend on both roughness amplitude and chordwise location. The Reynolds number based on element height is found to satisfactorily approximate the initial forcing amplitude, revealing the importance of local velocity effects in non-zero-pressure gradient flows. Direct estimation of initial perturbation amplitudes from nonlinear simulations suggests the existence of pertinent flow mechanisms in the element vicinity, active in conditioning the onset of modal instabilities. Dedicated velocimetry planes, elucidate the development of a momentum deficit wake which rapidly decays downstream of the element followed by mild growth, representing the first experimental evidence of transient behaviour in swept wing boundary layers. The outcome of this work identifies a strong scalability of the transition dynamics to roughness amplitude and location, warranting the upscaling of roughness elements to more accessible, measurable and spatially resolved configurations in future experiments.

Wave-shape function model order estimation by trigonometric regression

The adaptive non-harmonic (ANH) model is a powerful tool to compactly represent oscillating signals with time-varying amplitude and phase, and non-sinusoidal oscillating morphology. Given good estimators of instantaneous amplitude and phase we can construct an adaptive model, where the morphology of the oscillation is described by the wave-shape function (WSF), a 2π-periodic more general periodic function. In this paper, we address the problem of estimating the number of harmonic components of the WSF, a problem that remains underresearched, by adapting trigonometric regression model selection criteria into this context. We study the application of these criteria, originally developed in the context of stationary signals, to the case of signals with time-varying amplitudes and phases. We then incorporate the order estimation to the ANH model reconstruction procedure and analyze its performance for noisy AM-FM signals. Experimental results on synthetic signals indicate that these criteria enable the adaptive estimation of the waveform of non-stationary signals with non-sinusoidal oscillatory patterns, even in the presence of considerable amount of noise. We also apply our reconstruction procedure to the task of denoising simulated pulse wave signals and determine that the proposed technique performs competitively to other denoising schemes. We conclude this work by showing that our adaptive order estimation algorithm takes into account the interpatient waveform variability of the electrocardiogram (ECG) and respiratory signals by analyzing recordings from the Fantasia Database.

A Preliminary Study on the Use of HD-sEMG for the Functional Imaging of Equine Superficial Muscle Activation during Dynamic Mobilization Exercises.

Simple SummaryAn evidence-based approaches to assess the effect of rehabilitation protocols is currently under investigation in animal physiotherapy. Research aimed to identify objective outcome measurements are of major importance in this field. Functional muscle assessment remains challenging during the application of specific exercises to activate core muscles in horses. This study introduces for the first time the use of bi-dimensional High-Density Surface Electromyography (HD-sEMG) in horse as a non-invasive tool that provides a functional imaging of superficial skeletal muscle activation, and contraction. Using a 32 and/or 64 surface EMG electrode grids positioned on two superficial core muscles, a colour scale image obtained from recorded signals allowed visual assessment of muscle activation. The exercises used to test this technology were the destabilization exercise, the “chin-to-lateral” bending and the “chin-to-knees” flexion exercise. Our results support the use of HD-sEMG in equine physiotherapy to obtain an immediate biofeedback of muscle activation and objectively tracking the physiotherapy treatments.Superficial skeletal muscle activation is associated with an electric activity. Bidimensional High-Density Surface Electromyography (HD-sEMG) is a non-invasive technique that uses a grid of equally spaced electrodes applied on the skin surface to detect and portray superficial skeletal muscle activation. The goal of the study was to evaluate the feasibility of HD-sEMG to detect electrical activation of skeletal muscle and its application during rehabilitation exercises in horses. To fulfil this aim, activation of the superficial descending pectoral and external abdominal oblique core muscles were measured using HD-sEMG technology during dynamic mobilization exercises to induce lateral bending and flexion/extension tasks of the trunk. Masseter muscle was instrumented during mastication as a control condition. A 64 surface EMG channel wireless system was used with a single 64 electrode grid or a pair of 32 electrode grids. HD-sEMG provided unique information on the muscular activation onset, duration, and offset, along each motor task, and permitting inferences about the motor control strategy actuated by the central nervous system. Signals were further processed to obtain firing frequencies of few motor-neurons. Estimation of electromyographic amplitude and spectral parameters allowed detecting the onset of muscular fatigue during the motor tasks performed. HD-sEMG allows the assessment of muscular activation in horses performing specific motor tasks, supporting its future application in clinical and research settings.

Variational quantum amplitude estimation

We propose to perform amplitude estimation with the help of constant-depth quantum circuits that variationally approximate states during amplitude amplification. In the context of Monte Carlo (MC) integration, we numerically show that shallow circuits can accurately approximate many amplitude amplification steps. We combine the variational approach with maximum likelihood amplitude estimation [Y. Suzuki et al., Quantum Inf. Process. 19, 75 (2020)] in variational quantum amplitude estimation (VQAE). VQAE typically has larger computational requirements than classical MC sampling. To reduce the variational cost, we propose adaptive VQAE and numerically show in 6 to 12 qubit simulations that it can outperform classical MC sampling.

Optical Arbitrary Waveform Measurement (OAWM) Using Silicon Photonic Slicing Filters

We demonstrate an optical arbitrary waveform measurement (OAWM) system that exploits a bank of silicon photonic (SiP) frequency-tunable coupled-resonator optical waveguide (CROW) filters for gapless spectral slicing of broadband optical signals. The spectral slices are coherently detected using a frequency comb as a multi-wavelength local oscillator (LO) and stitched together by digital signal processing (DSP). For high-quality signal reconstruction, we have implemented a maximum-ratio combining (MRC) technique based on precise calibration of the complex-valued opto-electronic transfer functions of all detection paths. In a proof-of-concept experiment, we demonstrate the viability of the scheme by implementing a four-channel system that offers an overall detection bandwidth of 140 GHz. Exploiting a femtosecond laser with precisely known pulse shape for calibration along with dynamic amplitude and phase estimation, we reconstruct 100 GBd QPSK, 16QAM and 64QAM optical data signals. The reconstructed signals show improved quality compared to that obtained with a single high-speed intradyne receiver, while the electronic bandwidth requirements of the individual coherent receivers are greatly reduced.

Restoration of Cone Sensitivity to Individuals with Congenital Photoreceptor Blindness within the Phase 1/2 Sepofarsen Trial.

PurposeTo understand consequences of reconstituting cone photoreceptor function in congenital binocular blindness resulting from mutations in the centrosomal protein 290 (CEP290) gene.DesignPhase 1b/2 open-label, multicenter, multiple-dose, dose-escalation trial.ParticipantsA homogeneous subgroup of 5 participants with light perception (LP) vision at the time of enrollment (age range, 15–41 years) selected for detailed analyses. Medical histories of 4 participants were consistent with congenital binocular blindness, whereas 1 participant showed evidence of spatial vision in early life that was later lost.InterventionParticipants received a single intravitreal injection of sepofarsen (160 or 320 μg) into the study eye.Main Outcome MeasuresFull-field stimulus testing (FST), visual acuity (VA), and transient pupillary light reflex (TPLR) were measured at baseline and for 3 months after the injection.ResultsAll 5 participants with LP vision demonstrated severely abnormal FST and TPLR findings. At baseline, FST threshold estimates were 0.81 and 1.0 log cd/m2 for control and study eyes, respectively. At 3 months, study eyes showed a large mean improvement of –1.75 log versus baseline (P < 0.001), whereas untreated control eyes were comparable with baseline. Blue minus red FST values were not different than 0 (P = 0.59), compatible with cone mediation of remnant vision. At baseline, TPLR response amplitude and latency estimates were 0.39 mm and 0.72 seconds, respectively, for control eyes, and 0.28 mm and 0.78 seconds, respectively, for study eyes. At 3 months, study eyes showed a mean improvement of 0.44 mm in amplitude and a mean acceleration of 0.29 seconds in latency versus baseline (P < 0.001), whereas control eyes showed no significant change versus baseline. Specialized tests performed in 1 participant confirmed and extended the standardized results from all 5 participants.ConclusionsBy subjective and objective evidence, intravitreal sepofarsen provides improvement of light sensitivity for individuals with LP vision. However, translation of increased light sensitivity to improved spatial vision may occur preferentially in those with a history of visual experience during early neurodevelopment. Interventions for congenital lack of spatial vision in CEP290-associated Leber congenital amaurosis may lead to better results if performed before visual cortex maturity.

A study of the heave-induced surge and swap pressures when a drillstring is in the slips of a floating vessel

This study presents a theory describing surge and swab pressure when a drillstring is hanging in the slips of a heaving vessel. Downhole pressure measurement shows high pressure pulses in these instances, higher than can be explained with simple steady-state calculation. Several factors and parameters affect this pressure, such as annulus geometry, drillstring elasticity, wellbore friction, fluid compressibility, advanced fluid rheology, and fluid inertia. The advanced fluid rheology includes a flow-development phase and a simple fluid thixotropy model. The theoretical model is tested and compared with actual field data recorded at the surface and downhole, both pressure and string acceleration are measured. Key findings from this study are: (1) The annular flow is induced by the axial stick–slip motion of the bottomhole assembly; (2) The surge swab pressure consists of a pressure-loss term and an inertia term, where the latter is the dominating one in this case; (3) The short periods of the axial string motion call for a transient analysis to get an accurate estimate of the pressure amplitude. • Transient surge and swab model. • Stick slip induced pressure pulses. • Fast model for thixotropy and flow pattern development. • High resolution downhole measurements. Both string acceleration and downhole pressure.

Quantum algorithms for numerical differentiation of expected values with respect to parameters

The quantum algorithms for Monte Carlo integration (QMCI), which are based on quantum amplitude estimation (QAE), speed up expected value calculation compared with classical counterparts and have been widely investigated along with their applications to industrial problems such as financial derivative pricing. In this paper, we consider an expected value of a function of a stochastic variable and a real-valued parameter and how to calculate derivatives of the expectation with respect to the parameter. This problem is related to calculating sensitivities of financial derivatives and so of industrial importance. Based on QMCI and the general-order central difference formula for numerical differentiation, we propose two quantum methods for this problem and evaluate their complexities. The first one, which we call the naive iteration method, simply calculates the formula by iterative computations and additions of the terms in it and then estimates its expected value by QAE. The second one, which we name the sum-in-QAE method, performs the summation of the terms at the same time as the sum over the possible values of the stochastic variable in a single QAE. We see that, depending on the smoothness of the function and the number of qubits available, either of two methods is better than the other. In particular, when the function is nonsmooth or we want to save the qubit number, the sum-in-QAE method can be advantageous.

A Multicomponent Temporal Coherence Model for 3-D Phase Unwrapping in Time-Series InSAR of Seasonal Deformation Areas

3-D phase unwrapping (PU) methods based on the 2-D linear temporal coherencemodel have been widely used in time-series interferometric synthetic aperture radar (TS-InSAR) for measuring topography and monitoring subtle deformation. However, the linear temporal coherencemodel can not characterize the coherence of highly coherent pixels accurately in seasonal deformation areas, where nonlinear deformation is deterministic and nonnegligible. Especially, for urban areas with groundwater or thermal dilation seasonal changes or permafrost regions, the nonlinear deformation is usually associated with periodic temperature changes. In this work, a general multi-component temporal coherence model, which considers multiple components including the seasonal deformation, is proposed for 3-D PU of seasonal deformation areas. Moreover, the uncertainty evaluation criterion, based on Cramér–Rao bound (CRB), is derived for TS-InSAR. The experimental results, obtained by applying the multi-component temporal coherence model to a data set acquired from January 2012 to February 2016 over the Beijing Capital International Airport area, confirm the effectiveness of the proposed method. High phase consistency, accurate corrected digital elevation model (DEM) and deformation information monitoring with high-density and high-coverage PS pixels are achieved. Under the same iterations and TS-InSAR procedure, the enhanced performance by the proposed model is illustrated by comparing with that of linear model in terms of phase consistency of 3-D phase unwrapping, PSCs selection at each step, and final results evaluation. In summary, the number of phase-consistency edges after 3-D PU is increased by about 15%, the number of final PS pixels selected with the same coherence threshold constraint is increased by about 10%, and more PS pixels provide a low uncertainty in residual topography, mean deformation velocity and seasonal amplitude estimation.

Bi-regularization enhanced azimuthal mode analysis method for the aero-engine fan

Azimuthal mode analysis is regarded as an effective tool for aero-engine flow field investigation, where numerous microphones are evenly mounted as a ring to provide sufficient spatial resolution for azimuthal pressure acquisition. The current compressive sampling method enables azimuthal modes to be obtained from much fewer microphones, with dominant and non-dominant modes separately estimated by L1-norm regularization and spatial Fourier transform or least square method. Despite the effort of measurement system simplification, this classical compressive sampling method regularized by L1-norm inherently introduces accuracy loss in amplitude estimation for both dominant and non-dominant modes. With the aim of accuracy promotion and further measurement reduction, the Bi-regularization enhanced azimuthal mode analysis (BRAMA) method is devised to investigate the azimuthal modes of the aero-engine fan via limited acoustic measurements. The BRAMA method substitutes L1-norm regularization with Lp-norm (0<p<1) regularization to reach more accurate reconstruction of dominant modes. Meanwhile, the Tikhonov regularization based on L2-norm is introduced to estimate non-dominant modes. The effectiveness of the BRAMA method is verified in two cases, by operating a 2.5-stage aero-engine fan test rig at 50% and 90% of the nominal speed, respectively. Firstly, acoustic pressure signals are pre-processed to extract the dominant tonal component, which are used as the input of dominant mode estimation. Next, comparative realizations by L1-norm and Lp-norm are conducted to detect the dominant modes, meanwhile the amplitude accuracy with respect to p value and measurement number is discussed in both cases. Finally, non-dominant modes are estimated by using Tikhonov regularization in comparison to the classical approaches. Experimental results of both cases indicate that the BRAMA method outperforms the classical compressive sampling approach in accuracy improving, measurements reducing and interference proof capability.

Quantum pricing with a smile: implementation of local volatility model on quantum computer

Quantum algorithms for the pricing of financial derivatives have been discussed in recent papers. However, the pricing model discussed in those papers is too simple for practical purposes. It motivates us to consider how to implement more complex models used in financial institutions. In this paper, we consider the local volatility (LV) model, in which the volatility of the underlying asset price depends on the price and time. As in previous studies, we use the quantum amplitude estimation (QAE) as the main source of quantum speedup and discuss the state preparation step of the QAE, or equivalently, the implementation of the asset price evolution. We compare two types of state preparation: One is the amplitude encoding (AE) type, where the probability distribution of the derivative’s payoff is encoded to the probabilistic amplitude. The other is the pseudo-random number (PRN) type, where sequences of PRNs are used to simulate the asset price evolution as in classical Monte Carlo simulation. We present detailed circuit diagrams for implementing these preparation methods in fault-tolerant quantum computation and roughly estimate required resources such as the number of qubits and T-count.

Bermudan option pricing by quantum amplitude estimation and Chebyshev interpolation

Pricing of financial derivatives, in particular early exercisable options such as Bermudan options, is an important but heavy numerical task in financial institutions, and its speed-up will provide a large business impact. Recently, applications of quantum computing to financial problems have been started to be investigated. In this paper, we first propose a quantum algorithm for Bermudan option pricing. This method performs the approximation of the continuation value, which is a crucial part of Bermudan option pricing, by Chebyshev interpolation, using the values at interpolation nodes estimated by quantum amplitude estimation. In this method, the number of calls to the oracle to generate underlying asset price paths scales as widetilde{O}(epsilon ^{-1}), where ϵ is the error tolerance of the option price. This means the quadratic speed-up compared with classical Monte Carlo-based methods such as least-squares Monte Carlo, in which the oracle call number is widetilde{O}(epsilon ^{-2}).

Quantum algorithm for credit valuation adjustments

Quantum mechanics is well known to accelerate statistical sampling processes over classical techniques. In quantitative finance, statistical samplings arise broadly in many use cases. Here we focus on a particular one of such use cases, credit valuation adjustment (CVA), and identify opportunities and challenges towards quantum advantage for practical instances. To build a NISQ-friendly quantum circuit able to solve such problem, we draw on various heuristics that indicate the potential for significant improvement over well-known techniques such as reversible logical circuit synthesis. In minimizing the resource requirements for amplitude amplification while maximizing the speedup gained from the quantum coherence of a noisy device, we adopt a recently developed Bayesian variant of quantum amplitude estimation using engineered likelihood functions. We perform numerical analyses to characterize the prospect of quantum speedup in concrete CVA instances over classical Monte Carlo simulations.

Cascaded Least Square Algorithm for Strong Clutter Removal in Airborne Passive Radar

Owing to the continuous random and nonperiodic characteristics of the passive signal, the random range sidelobe coupling (RRSC) effects of the strong clutter (i.e., the direct path signal and the strong multipath signal) will exacerbate the performance of space-time adaptive processing (STAP) algorithm in airborne passive radar (APR). This article analyzes the influence of RRSC caused by strong clutter on detection range cell of interest and illustrates that strong clutter should be suppressed before applying the STAP algorithm. A cascaded least square (CLS) algorithm based on the directional dependence of clutter Doppler frequency is proposed for side-looking APR, where the first least square (LS) algorithm is performed to achieve the amplitude estimation of the Doppler-shift echo signal, and the channel amplitude and phase error correction factor can be obtained by the estimated amplitude information of the direct patch signal and the APR geometric configuration. The second LS is employed to further estimate the amplitude information of the strong clutter, and the resulting weight vector can be utilized for clutter cancelation. To make the CLS algorithm more practical, a batch version of the CLS (CLS-B) algorithm is proposed in this article. The advantage of the method is that it cannot only cancel clutter along the clutter ridge but also effectively prevent the suppression of targets falling in the clutter Doppler band. In addition, the proposed CLS algorithm performs well in the presence of the channel amplitude and phase error. A series of simulations are conducted to test the proposed algorithms.

확률적 정보량에 의한 표면근전도 진폭 추정 매개변수 평가

Optimal Amplitude estimation from the SEMG(surface electromyogram) signal is important because it can be used potential sources to control prosthetics and robotics. In this paper, four representative SEMG amplitude estimation parameters(ARV:average rectified value, RMS:root mean square, MTA:mean turn amplitude, MSA:mean spike amplitude) were evaluated based on probabilistic information theory, which determine the amount of information that each parameter is able to extract from SEMG signal. Surface EMG signals from eleven subjects were recorded in biceps brachii muscle with constant isometric 20, 50, and 80%MVC contractions. The parameters were investigated by the amount of mutual information between stimulus(contraction level) and response(amplitude estimation parameter) variables. Results of this study show there are no statistical significant differences(p<0.05) in the point of amount of information among the four variables. Although the evaluation method suggested here were applied to amplitude estimation parameters, it can also be considered as alternative tool to evaluate various processing technique in different areas of surface EMG analysis.

Application of a Heuristic Method to Solve Nonlinear Oscillators with Irrational Forces

This paper applies another amplitude-frequency relationship as of late established by Yazdi and Tehrani (Alexandria Engineering Journal 54 99-103, 2015) to analyze periodical solutions of nonlinear oscillators; such oscillators are considered emphatically nonlinear on the grounds that they contain an irrational force term. Estimation strategy is straightforward yet additionally helpful and its formulation depends on combining the energy balance technique with an uncommon collocation point. At long last, we uncover the convenience and proficiency of the proposed technique resolving three instances of conservative nonlinear oscillators in which the maximum relative error acquired is $2.5\%.$ Exposed models show that the strategy has a high precision to solve mechanical issues of both small and huge estimations of the oscillation amplitude. Finally, the methodology used can be very useful for the study of nonlinear oscillators in basic undergraduate physics and mechanics courses.