Recovered Signals Research Articles

Recovery of rectified signals from hot-wire/film anemometers due to flow reversal in oscillating flows

Hot-wire/film anemometers have been broadly used in experimental studies in fluid mechanics, acoustics, and ocean engineering. Yet, it is well known that hot-wire/film anemometers rectify the signal outputs due to the lack of sensitivity to flow direction. This main drawback, in turn, makes them less useful for diverse fluctuating flow measurements. To solve this issue, a rectification recovery method has been developed based on reconstruction of the Fourier series expansion in conjunction with signal-squaring approach. This signal recovery method was experimentally examined and proven to be successful for both conventional and microfabricated hot-wire/film anemometers. The method was further applied to dipole field measurements, with data from recovered signals perfectly matching the analytical model of the dipole field.

Independent source resolution: an alternative MEG figure of merit

Event Abstract Back to Event Independent source resolution: an alternative MEG figure of merit Stephen Robinson1* 1 Henry Ford Hospital, Athena project team, United States Independent source resolution (ISR) is a proposed method for characterizing the ability of a MEG sensor array and accompanying software to discriminate among signals arising from multiple closely spaced cortical sources. It is often stated that MEG can localize a single dipole source within a few millimeters. In practice, localization accuracy and source resolution depend upon signal-to-noise, the presence of interfering sources, and coregistration. Having excellent resolution of single sources does not necessarily imply resolution of multiple sources. The primary clinical application of MEG is localization of epileptic cortex. Invasive intracranial EEG is the standard for presurgical diagnosis. ECoG is used to identify the ictal onset zone (IOZ) by mapping normal and abnormal activity on a 10 mm grid. In order to determine if this can be achieved using existing MEG helmets, an array of 64 dipole sources was simulated on an 8x8 grid with 10 mm spacing. Each dipole was assigned an independent random time series. The MEG signal was then simulated using the forward solution for each source and adding simulated brain and sensor noise. Next, a scalar LCMV beamformer was used to estimate the source waveforms at the location of each dipole. Last, a matrix of the correlation of the simulated versus recovered signals is computed. The deviation of this matrix from the identity matrix provides a measure of ISR. This method was used to evaluate the performance of several whole-head MEG instruments and high resolution EEG. Results indicate that none of the existing MEG instruments or scalp EEG have sufficient ISR to substitute for ECoG grids. ISR of these instruments is limited by the gap between sensors and the cortex. A proposed high-resolution MEG sensor array with a smaller gap and inter-sensor spacing was also simulated and shown to have sufficient ISR for noninvasive IOZ mapping. This research was supported by NIH/NINDS Grant R01 NS30914. Conference: Biomag 2010 - 17th International Conference on Biomagnetism , Dubrovnik, Croatia, 28 Mar - 1 Apr, 2010. Presentation Type: Poster Presentation Topic: MEG Modeling Citation: Robinson S (2010). Independent source resolution: an alternative MEG figure of merit. Front. Neurosci. Conference Abstract: Biomag 2010 - 17th International Conference on Biomagnetism . doi: 10.3389/conf.fnins.2010.06.00049 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 Mar 2010; Published Online: 21 Mar 2010. * Correspondence: Stephen Robinson, Henry Ford Hospital, Athena project team, Detroit, United States, robinson@neurnis.neuro.hfh.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Stephen Robinson Google Stephen Robinson Google Scholar Stephen Robinson PubMed Stephen Robinson Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Performance of Feedback Cancellers for T-DMB On-Channel Repeaters

This paper presents a feedback canceller (FC) for T-DMB repeaters. Though the conventional FC of T-DMB repeaters has a good feedback cancellation performance, it distorts the recovered signal's out-band spectrum. This spectrum distortion problem is very crucial for commercializing T-DMB repeaters. The feedback canceller with pre-whitening filters (PWFs), which estimates the feedback channel using whitened input signals, can compensate this spectrum problem. However the feedback canceling performance degradation occurs when the feedback channel varies with Doppler effects. To compensate the out-band spectrum distortion and cope with the variation of feedback channel, we propose a novel FC based on the convex combination algorithm. Simulation results show that the proposed FC can remove clearly the out-band spectrum distortion of the recovered signal with improved the feedback canceling performance in both time-invariant and time-varying feedback channels.

Localization and recovery of peripheral neural sources with beamforming algorithms.

The peripheral nervous system carries sensory and motor information that could be useful as command signals for function restoration in areas such as neural prosthetics and functional electrical stimulation (FES). Nerve cuff electrodes provide a robust and safe technique for recording nerve signals. However, a method to separate and recover signals from individual fascicles is necessary. Prior knowledge of the electrode geometry was used to develop an algorithm which assumes neither signal independence nor detailed knowledge of the nerve's geometry/conductivity, and is applicable to any wide-band near-field situation. When used to recover fascicular activities from simulated nerve cuff recordings in a realistic human femoral nerve model, this beamforming algorithm separates signals as close as 1.5 mm with cross-correlation coefficient, R > 0.9 (10% noise). Ten simultaneous signals could be recovered from individual fascicles with only a 20% decrease in R compared to a single signal. At high noise levels (40%), sources were localized to 180 +/- 170 microm in the 12 x 3 mm cuff. Localizing sources and using the resulting positions in the recovery algorithm yielded R = 0.66 +/- 0.10 in 10% noise for five simultaneous muscle-activation signals from synergistic fascicles. These recovered signals should allow natural, robust, closed-loop control of multiple degree-of-freedom prosthetic devices and FES systems.

6-단자 위상 상관기를 이용한 PSK 반송파 신호 복원 회로 해석

The PSK carrier signal recovery circuit using a six-port phase correlator was analyzed and the circuit structure is proposed in this paper. The proposed carrier signal recovery circuit that is made of reflection element and six-port phase correlator, which is comprised of a power divider and three hybrid branch line couplers, give a simple structure and can be fabricated without no difficulty. The circuit recovers the carrier signal of BPSK and QPSK modulation signal. The proposed scheme can be utilized as a basis structure for high-mode PSK carrier signal recovery. By simulation results, the recovered signal by the proposed circuit shows a good carrier signal characteristic with CW signal of a constant phase() and phase error due to glitch conditions.

Decontamination of cosmological 21-cm maps

We present a method for extracting the expected cosmological 21-cm signal from the epoch of re-ionization, taking into account contaminating radiations and random instrumental noise. The method is based on the maximum a posteriori probability (MAP) formalism and employs the coherence of the contaminating radiation along the line-of-sight and the three-dimensional correlations of the cosmological signal. We test the method using a detailed and comprehensive modelling of the cosmological 21-cm signal and the contaminating radiation. The signal is obtained using a high-resolution N-body simulation where the gas is assumed to trace the dark matter and is re-ionized by stellar radiation computed from semi-analytic galaxy formation recipes. We model contaminations to the cosmological signal from synchrotron and free–free galactic foregrounds and extragalactic sources including active galactic nuclei, radio haloes and relics, synchrotron and free–free emission from star-forming galaxies and free–free emission from dark matter haloes and the intergalactic medium. We provide tests of the reconstruction method for several rms values of instrumental noise from σN= 1 to 250 mK. For low instrumental noise, the recovered signal, along individual lines-of-sight, fits the true cosmological signal with a mean rms difference of drms≈ 1.7 ± 0.6 for σN= 1 mK, and drms≈ 4.2 ± 0.4 for σN= 5 mK. The one-dimensional power spectrum is nicely reconstructed for all values of σN considered here, while the reconstruction of the two-dimensional power spectrum and the Minkowski functionals is good only for noise levels of the order of few mK.

Adaptive separation of free-surface multiples through independent component analysis

We present a three-stage algorithm for adaptive separation of free-surface multiples. The free-surface multiple elimination (FSME) method requires, as deterministic prerequisites, knowledge of the source wavelet and deghosted data. In their absence, FSME provides an estimate of free-surface multiples that must be subtracted adaptively from the data. First we construct several orders from the free-surface multiple prediction formula. Next we use the full recording duration of any given data trace to construct filters that attempt to match the data and the multiple predictions. This kind of filter produces adequate phase results, but the order-by-order nature of the free-surface algorithm brings results that remain insufficient for straightforward subtraction. Then we construct, trace by trace, a mixing model in which the mixtures are the data trace and its orders of multiple predictions. We separate the mixtures through a blind source separation technique, in particular by employing independent component analysis. One of the recovered signals is a data trace without free-surface multiples. This technique sidesteps the subtraction inherent in most adaptive subtraction methods by separating the desired signal from the free-surface multiples. The method was applied to synthetic and field data. We compared the field data to a published method and found comparable results.

Use of Independent Component Analysis to Reduce Motion Artifact in Pulse Transit Time Measurement

Motion artifact is a common occurrence that contaminates physiologic measurements such as pulse transit time (PTT). Furthermore, some advanced signal processing algorithms used in artifact management can induce unwanted errors in the timing characteristics of the recovered signals. In order to extract useful timing information, an independent component analysis algorithm based on the minimization of mutual information approach is used to post-process artifact-induced signals used in PTT computations. Experimental results from two unregulated movements demonstrated the efficacy of the proposed method in computing PTT measurements.

A new blind deconvolution algorithm based on the probability distribution method

AbstractBlind deconvolution is a method of recovering transmitted signals from only received signals. The probability distribution method is one of the blind deconvolution methods. This method has two problems: it has slower convergence and its reliability is lower. In this paper, we propose a new algorithm for solving these two problems. The proposed algorithm is as follows. (1) It is based on the adaptive processing with each sample. (2) Kurtosis is adaptively estimated by recovered signals with each sample. (3) Cost function is decided by kurtosis. (4) Transmitted signals are recovered by received signals using decided cost function on the sample time. We confirm the validity of the new algorithm by computer simulation. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 162(1): 56–65, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20317

Analysis and Online Realization of the CCA Approach for Blind Source Separation

A critical analysis of the canonical correlation analysis (CCA) approach in blind source separation (BSS) is provided. It is proved that by maximizing the autocorrelation functions of the recovered signals we can separate the source signals successfully. It is further shown that the CCA approach represents the same class of generalized eigenvalue decomposition (GEVD) problems as the matrix pencil method. Finally, online realizations of the CCA approach are discussed with a linear-predictor-based algorithm studied as an example.

Blind separation of mixed-kurtosis signals using soft switch activation function

A soft switch nonlinear activation function for the blind separation of signals with mixed kurtosis signs is presented. The parameter of the nonlinear activation function is adaptively determined during the blind separation process, which does not need to estimate the kurtosis of the recovered signals. Numerical simulations demonstrate that the proposed algorithm is suitable for recovering sub-Gaussian, Gaussian and super-Gaussian signals from their mixtures.

Modeling and Compensating Input Distortion in MIMO Systems via Blind Deconvolution

This paper proposes a method for modeling and compensating nonlinear input distortion in MIMO dynamical systems. This is conducted in three steps. First, the distorted signals are recovered from the observed output by using blind signal deconvolution based on statistical independence of the input signals. The linear part of the system is also identified in this first step. Secondly, the recovered signal, together with the input signal, gives a model of distortion as a nonlinear function. Finally the distortion is compensated by applying the inverse of the estimated function.

Study of Geophysical Parameters by Well Information-Measuring Systems on Regenerative Sources

The information-measuring system is intended to continuously determine a set of geophysical parameters of worked-out areas of running oil reservoirs under pressures of up to 100 mPa. The system consists of ground and well telemeter units, and an acoustic waveguide based on a well scratcher wire is used as a communication link between them. Due to the permanent connection of the housing of the well instrument and scratcher wire and the use of a power supply unit based on a current generator in the form of a spinner rotameter with rotor and stator windings, the well instrument is self-contained and can operate in hostile environments with pressure differences of up to 20 mPa. The measurement ranges are as follows: for the flow velocity sensor, the range is 0.001–0.1 m/s with a 0.5% error; for the pressure gage, it is 0–90 mPa with a 0.1% error; for the temperature sensor, the range is 0–125°C with a 0.1% error; and for the humidity sensor, it is within a humidity range of 50.1–99.9% with a 0.1% error. These systems are multichannel due to the self-synchronization method of the recovered signals of the sensors in the ground part with a 0.1% total reception/transmission error determined by the analog-to-digital conversion.

Surface wave tomography from seismic ambient noise in Southern California

It has been demonstrated experimentally that an estimate of the Green’s tensor between two seismic stations can be obtained from the long-time average of the cross-correlation of ambient noise at the two stations. This result provides a means to image Earth structure using the ambient noise field only, without the use of active seismic sources or earthquakes. Seismic noise data from 148 broadband seismic stations in Southern California were used to extract the surface wave arrival-times between all station pairs in the network in the frequency band 0.05–0.4 Hz. In this frequency band, ambient noise (originating from ocean microseisms) propagating over long distances is typically dominated by surface waves. A record section of the waveforms as a function of increasing receiver separation shows clearly that the recovered signals are propagating wavetrains. The seismic data were then used in a simple, but densely sampled tomographic procedure to estimate the surface wave velocity structure for a region in Southern California. The result compares favorably with previous estimates obtained using more conventional and elaborate inversion procedures. This demonstrates that coherent ambient noise between station pairs can be used for seismic imaging purposes.

Resolving mass flux at high spatial and temporal resolution using GRACE intersatellite measurements

The GRACE mission is designed to monitor mass flux on the Earth's surface at one month and high spatial resolution through the estimation of monthly gravity fields. Although this approach has been largely successful, information at submonthly time scales can be lost or even aliased through the estimation of static monthly parameters. Through an analysis of the GRACE data residuals, we show that the fundamental temporal and spatial resolution of the GRACE data is 10 days and 400 km. We present an approach similar in concept to altimetric methods that recovers submonthly mass flux at a high spatial resolution. Using 4° × 4° blocks at 10‐day intervals, we estimate the mass of surplus or deficit water over a 52° × 60° grid centered on the Amazon basin for July 2003. We demonstrate that the recovered signals are coherent and correlate well with the expected hydrological signal.

Resistance, Capacitance, and Electrode Kinetic Effects in Fourier-Transformed Large-Amplitude Sinusoidal Voltammetry: Emergence of Powerful and Intuitively Obvious Tools for Recognition of Patterns of Behavior

Large-amplitude sinusoidal ac voltammetric techniques, when analyzed in the frequency domain using the Fourier transform-inverse Fourier transform sequence, produce the expected dc and fundamental harmonic ac responses in addition to very substantial second, third, and higher ac harmonics that arise from the presence of significant nonlinearity. A full numerical simulation of the process, Red right arrow over left arrow Ox + e(-), incorporates terms for the uncompensated resistance (R(u)), capacitance of the double layer (C(dl)), and slow electron transfer kinetics (in particular, the reversible potential (E degrees ), rate constant (k(0)), and charge transfer coefficient (alpha) from the Butler-Volmer model). Identification of intuitively obvious patterns of behavior (with characteristically different sensitivity regimes) in dc, fundamental, and higher harmonic terms enables simple protocols to be developed to estimate R(u), C(dl), E degrees , k(0), and alpha. Thus, if large-amplitude sinusoidal cyclic voltammograms are obtained for two concentrations of the reduced species, data obtained from analysis of the recovered signals provide initial estimates of parameters as follows: (a) the dc cyclic component provides an estimate of E degrees (because the R(u) and k(0) effects are minimized); (b) the fundamental harmonic provides an estimate of C(dl) (because it has a high capacitance-to-faradaic current ratio); and (c) the second harmonic provides an estimate of R(u), k(0), and alpha (because the C(dl) effect is minimized). Methods of refining the initial estimates are then implemented. As a check on the fidelity of the parameters (estimated on the basis of an essentially heuristic approach that solely utilizes the dc, fundamental, and second harmonic voltammograms), comparison of the predicted simulated and experimental third (or higher) harmonic voltammograms can be made to verify that agreement between theory and experiment has been achieved at a predetermined level. The use of the heuristic pattern recognition approach to evaluate the oxidation of ferrocene at a platinum electrode (a reversible process) in the very high resistance solvent dichloromethane (0.1 M Bu(4)NPF(6)) and the reduction of [Fe(CN(6))](3)(-) at a glassy carbon electrode (a quasi-reversible process) in much lower resistance but higher capacitance conditions found in aqueous (0.5 M KCl) media is described and verifies the inherent advantages of employing large-amplitude sinusoidal techniques in quantitative studies of electrode processes.

Stochastic resonance and signal recovery in two-dimensional arrays of coupled oscillators

In this article, some prominent phenomena in a two-dimensional square array of coupled nonlinear oscillators driven by a periodic signal plus white noise are presented: (i) For a subthreshold periodic signal ( A ⩽ 1 - b ), besides conventional stochastic resonance (SR) as a best cooperative result of noise and periodic forcing, there also exists spontaneous SR induced purely by noise itself. The effects of these two SR phenomena are shown to be much better than those in the uncoupled case. (ii) For a superthreshold periodic driving ( A > 1 - b ), a certain amount of noise cannot only recover the concealed deterministic signal at the input frequency, but also significantly enhance the recovered signal to several times higher via the happening of SR. This phenomenon of SR is shown to be impossible in a single oscillator system.

Foetal ECG recovery using dynamic neural networks

Non-invasive electrocardiography has proven to be a very interesting method for obtaining information about the foetus state and thus to assure its well-being during pregnancy. One of the main applications in this field is foetal electrocardiogram (ECG) recovery by means of automatic methods. Evident problems found in the literature are the limited number of available registers, the lack of performance indicators, and the limited use of non-linear adaptive methods. In order to circumvent these problems, we first introduce the generation of synthetic registers and discuss the influence of different kinds of noise to the modelling. Second, a method which is based on numerical (correlation coefficient) and statistical (analysis of variance, ANOVA) measures allows us to select the best recovery model. Finally, finite impulse response (FIR) and gamma neural networks are included in the adaptive noise cancellation (ANC) scheme in order to provide highly non-linear, dynamic capabilities to the recovery model. Neural networks are benchmarked with classical adaptive methods such as the least mean squares (LMS) and the normalized LMS (NLMS) algorithms in simulated and real registers and some conclusions are drawn. For synthetic registers, the most determinant factor in the identification of the models is the foetal–maternal signal-to-noise ratio (SNR). In addition, as the electromyogram contribution becomes more relevant, neural networks clearly outperform the LMS-based algorithm. From the ANOVA test, we found statistical differences between LMS-based models and neural models when complex situations (high foetal–maternal and foetal-noise SNRs) were present. These conclusions were confirmed after doing robustness tests on synthetic registers, visual inspection of the recovered signals and calculation of the recognition rates of foetal R-peaks for real situations. Finally, the best compromise between model complexity and outcomes was provided by the FIR neural network. Both the methodology for selecting a model and the introduction of advanced neural models are the main contributions of this paper.

Testing the LIGO inspiral analysis with hardware injections

Injection of simulated binary inspiral signals into detector hardware provides an excellent test of the inspiral detection pipeline. By recovering the physical parameters of an injected signal, we test our understanding of both instrumental calibration and the data analysis pipeline. We describe an inspiral search code and results from hardware injection tests and demonstrate that injected signals can be recovered by the data analysis pipeline. The parameters of the recovered signals match those of the injected signals.

High-resolution multiproxy climatic records from ice cores, tree-rings, corals and documentary sources using eigenvector techniques and maps: assessment of recovered signal and errors

Palaeotemperature sensitive series from tree-rings, ice cores, corals and documentary sources are combined to producepalaeo summer-temperaturereconstructions (AD 1970-1761)and geographical eigenvector (EOF) maps in both hemispheres. They are compared favourably to those of existing summer-temperature average series. There are 51 palaeoseries in the Northern Hemisphere (mostly north of 40° N) and 16 series in the Southern Hemisphere. The statistics and significance of the palaeoreconstructions are examined by: (1) finding the correlation coefficient (palaeo to measured) as a function of the number and geographical distribution of the palaeo series; (2) developing and running a multiproxy model that generates pseudo series containing a signal and the same types and amounts of noise found in the various real palaeo series. The model reproduces the measured correlation coefficients and the eigenvector's (EOF) explained variances as functions of the number of sites. About 77% of the signal variance can be recovered with 51 well-distributed palaeo series and about 90% with greater than 100 series. The 1st eigenvector (EOF l) component maps in the Northern and Southern Hemispheres are fundamentally different, with the Northern having much less longitudinal variation than the Southern. This means (statistically) that simple hemispheric averages of summer temperature have more meaning in the Northern Hemisphere than in the Southern. Even though the various palaeoseries have different spectral biases, noise types and amounts, they were all used together and the common signal extracted. The results of this work strongly suggest that the multiproxy method is valid and that with enough sites most of the summer signal and geographical pattern can be extracted.