Coherent Averaging Research Articles

Neural network-based adaptive noise cancellation for enhancement of speech auditory brainstem responses

The measurement of the speech-evoked auditory brainstem response (speech ABR) is a promising technique for evaluating auditory function. However, the speech ABR is severely contaminated by background noise related to other brain electrical activity. The most commonly used method to enhance the signal-to-noise ratio (SNR) of the response is coherent averaging, while recently adaptive filtering has also been reported. All of the applied methods are based on linear operations, but since the assumption of linearity may not be valid for neural activity, linear methods may not be adequate. In this paper, we present a new nonlinear adaptive noise cancellation (ANC) based on a multilayer perceptron neural network to enhance the speech ABR and compare its performance with a linear ANC algorithm based on least mean squares adaptive filtering. The effectiveness of the methods is tested using speech ABR data and is based on two different types of SNR measures, the local SNR at the fundamental frequency of the response and the overall SNR. The results show that the nonlinear neural network-based ANC can reduce the required recording time and performs better than the linear ANC especially when the SNR of the recorded speech ABR is low.

Cerebrovascular effects of the thigh cuff maneuver.

Arterial hypotension can be induced by sudden release of inflated thigh cuffs (THC), but its effects on the cerebral circulation have not been fully described. In nine healthy subjects [aged 59 (9) yr], bilateral cerebral blood flow velocity (CBFV) was recorded in the middle cerebral artery (MCA), noninvasive arterial blood pressure (BP) in the finger, and end-tidal CO2 (ETCO2) with nasal capnography. Three THC maneuvers were performed in each subject with cuff inflation 20 mmHg above systolic BP for 3 min before release. Beat-to-beat values were extracted for mean CBFV, BP, ETCO2 , critical closing pressure (CrCP), resistance-area product (RAP), and heart rate (HR). Time-varying estimates of the autoregulation index [ARI(t)] were also obtained using an autoregressive-moving average model. Coherent averages synchronized by the instant of cuff release showed significant drops in mean BP, CBFV, and RAP with rapid return of CBFV to baseline. HR, ETCO2 , and ARI(t) were transiently increased, but CrCP remained relatively constant. Mean values of ARI(t) for the 30 s following cuff release were not significantly different from the classical ARI [right MCA 5.9 (1.1) vs. 5.1 (1.6); left MCA 5.5 (1.4) vs. 4.9 (1.7)]. HR was strongly correlated with the ARI(t) peak after THC release (in 17/22 and 21/24 recordings), and ETCO2 was correlated with the subsequent drop in ARI(t) (19/22 and 20/24 recordings). These results suggest a complex cerebral autoregulatory response to the THC maneuver, dominated by myogenic mechanisms and influenced by concurrent changes in ETCO2 and possible involvement of the autonomic nervous system and baroreflex.

Elastic metamaterials and dynamic homogenization: a review

In this paper, we review the recent advances which have taken place in the understanding and applications of acoustic/elastic metamaterials. Metamaterials are artificially created composite materials which exhibit unusual properties that are not found in nature. We begin with presenting arguments from discrete systems which support the case for the existence of unusual material properties such as tensorial and/or negative density. The arguments are then extended to elastic continuums through coherent averaging principles. The resulting coupled and nonlocal homogenized relations, called the Willis relations, are presented as the natural description of inhomogeneous elastodynamics. They are specialized to Bloch waves propagating in periodic composites and we show that the Willis properties display the unusual behavior which is often required in metamaterial applications such as the Veselago lens. We finally present the recent advances in the area of transformation elastodynamics, charting its inspirations from transformation optics, clarifying its particular challenges, and identifying its connection with the constitutive relations of the Willis and the Cosserat types.

Coherent and stochastic averaging in solid-state NMR

A new approach for calculating solid-state NMR lineshapes of uniaxially rotating membrane proteins under the magic-angle spinning conditions is presented. The use of stochastic Liouville equation (SLE) allows one to account for both coherent sample rotation and stochastic motional averaging of the spherical dipolar powder patterns by uniaxial diffusion of the spin-bearing molecules. The method is illustrated via simulations of the dipolar powder patterns of rigid samples under the MAS conditions, as well as the recent method of rotational alignment in the presence of both MAS and rotational diffusion under the conditions of dipolar recoupling. It has been found that it is computationally more advantageous to employ direct integration over a spherical grid rather than to use a full angular basis set for the SLE solution. Accuracy estimates for the bond angles measured from the recoupled amide 1H–15N dipolar powder patterns have been obtained at various rotational diffusion coefficients. It has been shown that the rotational alignment method is applicable to membrane proteins approximated as cylinders with radii of approximately 20Å, for which uniaxial rotational diffusion within the bilayer is sufficiently fast and exceeds the rate 2×105s−1.

Absolute intensity calibration of the 32-channel heterodyne radiometer on experimental advanced superconducting tokamak.

This paper presents the results of the in situ absolute intensity calibration for the 32-channel heterodyne radiometer on the experimental advanced superconducting tokamak. The hot/cold load method is adopted, and the coherent averaging technique is employed to improve the signal to noise ratio. Measured spectra and electron temperature profiles are compared with those from an independent calibrated Michelson interferometer, and there is a relatively good agreement between the results from the two different systems.

Detection and Estimation of Radar Reflectivity from Weak Echo of Precipitation in Dual-Polarized Weather Radars

Abstract In operational weather radar, precipitation echoes are often weak when compared to the underlying noise. Coherence properties of dual polarization can be used for enhancing the detection and for the improved estimation of weak echoes of precipitation. The enhanced detectability results from utilizing coherent averages of precipitation signals, while the uncorrelated noise vanishes asymptotically, explicit in the off-diagonal element Rhv of the echo covariance matrix. In finite sums, the noise terms as well as the uncertainties associated with them are suppressed. A signal can be detected in weaker echo by an analytically derived censoring policy. The coherent sums are readily available as the cross-correlation function of the antenna voltages H and V, which estimates Rhv in the mode of simultaneous transmission and reception. The magnitude of Rhv is a consistent estimate of the copolar echo power, leading to the copolar radar reflectivity of precipitation, which refers to the geometric mean of the reflectivities in H and V polarizations. Because of the intrinsic noise suppression, estimates of the copolar reflectivity are, in relative terms, more precise and more accurate than the corresponding estimates of reflectivity in specific channels, for weak signals of precipitation. These aspects are discussed quantitatively with validation of the key features in real conditions. The advances suggest for dedicated dual-polarization surveillance scans of weak echo of precipitation.

Adaptive coherent averaging for real-time electrocardiogram enhancement.

This paper presents an adaptive coherent averaging structure capable of removing broad-band interference from the electrocardiogram (ECG) while preserving the morphological features of the signal. The proposed structure improves the signal-to-noise ratio (SNR) of the adaptive line enhancer (ALE) while maintaining robustness to quasi-periodic signals. The least mean-square (LMS) and recursive least-square (RLS) adaptive algorithms are implemented. Analysis and comparison of the results is provided, leading to an optimized hybrid implementation. The cascade nature of the proposed structure is both scalable and suitable for implementation in real-time hardware.

Heterodyne Multifrequency Receiver for MST

Recently, a real-time and portable 2-D microwave imaging system operating at 24 GHz, incorporating modulation schemes similar to modulated scatterer technique and synthetic aperture radar (SAR) imaging technique, was designed using a heterodyne receiver with superior performance compared with a homodyne receiver. Multifrequency SAR images have the added advantage of providing for: 1) coherent averaging of image data over frequency and hence increasing system signal-to-noise ratio (SNR) and 2) enable volumetric (3-D) image production. This letter describes modifications to this receiver for enabling multifrequency operation through phase uncertainty (PU) analysis. These modifications show significant reduction in PU, thereby allowing the coherent addition of data necessary for SAR image formation with higher overall SNR.

Photoacoustic correlation signal-to-noise ratio enhancement by coherent averaging and optical waveform optimization

Photoacoustic (PA) imaging of biological tissues using laser diodes instead of conventional Q-switched pulsed systems provides an attractive alternative for biomedical applications. However, the relatively low energy of laser diodes operating in the pulsed regime, results in generation of very weak acoustic waves, and low signal-to-noise ratio (SNR) of the detected signals. This problem can be addressed if optical excitation is modulated using custom waveforms and correlation processing is employed to increase SNR through signal compression. This work investigates the effect of the parameters of the modulation waveform on the resulting correlation signal and offers a practical means for optimizing PA signal detection. The advantage of coherent signal averaging is demonstrated using theoretical analysis and a numerical model of PA generation. It was shown that an additional 5-10 dB of SNR can be gained through waveform engineering by adjusting the parameters and profile of optical modulation waveforms.

Robust Coherent Noise Suppression by Point Estimation of the Cauchy Location Parameter

This paper introduces a new point estimation algorithm, with particular focus on coherent noise suppression, given several measurements of the device under test where it is assumed that 1) the noise is first-order stationery and 2) the device under test is linear and time-invariant. The algorithm exploits the robustness of the Pitman estimator of the Cauchy location parameter through the initial scaling of the test signal by a centred Gaussian variable of predetermined variance. It is illustrated through mathematical derivations and simulation results that the proposed algorithm is more accurate and consistently robust to outliers for different tailed density functions than the conventional methods of sample mean (coherent averaging technique) and sample median search. Keywords—Central limit theorem, Fisher-Cramer Rao, gamma function, Pitman estimator.

FID modulus: a simple and efficient technique to phase and align MR spectra

The post-processing of MR spectroscopic data requires several steps more or less easy to automate, including the phase correction and the chemical shift assignment. First, since the absolute phase is unknown, one of the difficulties the MR spectroscopist has to face is the determination of the correct phase correction. When only a few spectra have to be processed, this is usually performed manually. However, this correction needs to be automated as soon as a large number of spectra is involved, like in the case of phase coherent averaging or when the signals collected with phased array coils have to be combined. A second post-processing requirement is the frequency axis assignment. In standard mono-voxel MR spectroscopy, this can also be easily performed manually, by simply assigning a frequency value to a well-known resonance (e.g. the water or NAA resonance in the case of brain spectroscopy). However, when the correction of a frequency shift is required before averaging a large amount of spectra (due to B 0 spatial inhomogeneities in chemical shift imaging, or resulting from motion for example), this post-processing definitely needs to be performed automatically. Zero-order phase and frequency shift of a MR spectrum are linked respectively to zero-order and first-order phase variations in the corresponding free induction decay (FID) signal. One of the simplest ways to remove the phase component of a signal is to calculate the modulus of this signal: this approach is the basis of the correction technique presented here. We show that selecting the modulus of the FID allows, under certain conditions that are detailed, to automatically phase correct and frequency align the spectra. This correction technique can be for example applied to the summation of signals acquired from combined phased array coils, to phase coherent averaging and to B 0 shift correction. We demonstrate that working on the modulus of the FID signal is a simple and efficient way to both phase correct and frequency align MR spectra automatically. This approach is particularly well suited to brain proton MR spectroscopy.

Coherent averaging in the frequency domain.

Quantum-mechanical evolution of systems with periodic time-modulated Hamiltonians is often described by effective interactions. Such average Hamiltonians, calculated as few terms of an expansion in powers of the interaction, are sometimes difficult to relate to experimental observations. We propose a frequency-domain approach to this problem, which offers certain advantages and produces an approximate solution for the density matrix, better linked to measurable quantities. The formalism is suitable for calculating the intensities of narrowed spectral peaks. Fast magic-angle-spinning NMR spectra of solids are used to experimentally illustrate the method.

Acoustic impulse response method as a source of undergraduate research projects and advanced laboratory experiments

A straightforward and inexpensive implementation of acoustic impulse response measurement is described utilizing the signal processing technique of coherent averaging. The technique is capable of high signal-to-noise measurements with personal computer data acquisition equipment, an amplifier/speaker, and a high quality microphone. When coupled with simple waveguide test systems fabricated from commercial PVC plumbing pipe, impulse response measurement has proven to be ideal for undergraduate research projects-often of publishable quality-or for advanced laboratory experiments. The technique provides important learning objectives for science or engineering students in areas such as interfacing and computer control of experiments; analog-to-digital conversion and sampling; time and frequency analysis using Fourier transforms; signal processing; and insight into a variety of current research areas such as acoustic bandgap materials, acoustic metamaterials, and fast and slow wave manipulation.

Control of cardiovascular variability during undisturbed wake-sleep behavior in hypocretin-deficient mice

The central neural mechanisms underlying differences in cardiovascular variability between wakefulness, non-rapid-eye-movement sleep (NREMS), and rapid-eye-movement sleep (REMS) remain poorly understood. These mechanisms may involve hypocretin (HCRT)/orexin signaling. HCRT signaling is linked to wake-sleep states, involved in central autonomic control, and impaired in narcoleptic patients. Thus, we investigated whether HCRT signaling plays a role in controlling cardiovascular variability during spontaneous behavior in HCRT-deficient mice. HCRT-ataxin3 transgenic mice lacking HCRT neurons (TG), knockout mice lacking HCRT peptides (KO), and wild-type controls (WT) were instrumented with electrodes for sleep recordings and a telemetric blood pressure transducer. Fluctuations of systolic blood pressure (SBP) and heart period (HP) during undisturbed wake-sleep behavior were analyzed with the sequence technique, cross-correlation functions, and coherent averaging of SBP surges. During NREMS, all mice had lower SBP variability, greater baroreflex contribution to HP control at low frequencies, and greater amplitude of the central autonomic and baroreflex changes in HP associated with SBP surges than during wakefulness. During REMS, all mice had higher SBP variability and depressed central autonomic and baroreflex HP controls relative to NREMS. HP variability during REMS was higher than during NREMS in WT only. TG and KO also had lower amplitude of the cardiac baroreflex response to SBP surges during REMS than WT. These results indicate that chronic lack of HCRT signaling may cause subtle alterations in the control of HP during spontaneous behavior. Conversely, the integrity of HCRT signaling is not necessary for the occurrence of physiological sleep-dependent changes in SBP variability.

Isolating scattering resonances of an air-filled spherical shell using iterative, single-channel time reversal

Iterative, single-channel time reversal is employed to isolate backscattering resonances of an air-filled spherical shell in a frequency range of 0.5-20 kHz. Numerical simulations of free-field target scattering suggest improved isolation of the dominant target response frequency in the presence of varying levels of stochastic noise, compared to processing returns from a single transmission and also coherent averaging. To test the efficacy of the technique in a realistic littoral environment, monostatic scattering experiments are conducted in the Gulf of Mexico near Panama City, Florida. The time reversal technique is applied to returns from a hollow spherical shell target sitting proud on a sandy bottom in 14 m deep water. Distinct resonances in the scattering response of the target are isolated, depending upon the bandwidth of the sonar system utilized.

Coherent averaging of the passive fathometer response using short correlation time

The passive fathometer algorithm was applied to data from two drifting array experiments in the Mediterranean, Boundary 2003 and 2004. The passive fathometer response was computed with correlation times from 0.34 to 90 s and, for correlation times less than a few seconds, the observed signal-to-noise ratio (SNR) agrees with a 1D model of SNR of the passive fathometer response in an ideal waveguide. In the 2004 experiment, the fathometer response showed the array depth varied periodically with an amplitude of 1 m and a period of 7 s consistent with wave driven motion of the array. This introduced a destructive interference, which prevents the SNR growing with increasing correlation time. A peak-tracking algorithm applied to the fathometer response of experimental data was used to remove this motion allowing the coherent passive fathometer response to be averaged over several minutes without destructive interference. Multirate adaptive beamforming, using 90 s correlation time to form adaptive steer vectors which were applied to 0.34 s data snapshots, increases the SNR of the passive fathometer response.

Coherent averaging of the passive fathometer response using short correlation time

The passive fathometer algorithm was applied to data from two drifting array experiments in the Mediterranean, Boundary 2003 and 2004. The passive fathometer response was computed with correlation times from 0.34 to 90 s and, for correlation times less than a few seconds, the observed signal-to-noise ratio (SNR) agrees with a 1 D model of SNR of the passive fathometer response in an ideal waveguide. In the 2004 experiment, the fathometer response showed the array depth varied periodically with an amplitude of 1 m and a period of 7 s consistent with wave driven motion of the array. This introduced a destructive interference, which prevents the SNR growing with increasing correlation time. A peak-tracking algorithm applied to the fathometer response of experimental data was used to remove this motion allowing the coherent passive fathometer response to be averaged over several minutes without destructive interference. Multirate adaptive beamforming, using 90 s correlation time to form adaptive steer vectors which were applied to 0.34 s data snapshots, increases the SNR of the passive fathometer response.

Feature Extraction on Brain Computer Interfaces using Discrete Dyadic Wavelet Transform: Preliminary Results

The purpose of this work is to evaluate different feature extraction alternatives to detect the event related evoked potential signal on brain computer interfaces, trying to minimize the time employed and the classification error, in terms of sensibility and specificity of the method, looking for alternatives to coherent averaging. In this context the results obtained performing the feature extraction using discrete dyadic wavelet transform using different mother wavelets are presented. For the classification a single layer perceptron was used. The results obtained with and without the wavelet decomposition were compared; showing an improvement on the classification rate, the specificity and the sensibility for the feature vectors obtained using some mother wavelets.

Single-Carrier Transmission Using Overlap Frequency Domain Equalizing and Coherent Averaging

This paper proposes a single-carrier transmission method based on an overlap frequency-domain equalizing (FDE) and a coherent averaging. FDE is a block-based equalizing technique using discrete Fourier transform. A cyclic prefix is often used to avoid inter-block interference under multipath channel conditions, which reduces transmission efficiency. An overlap FDE is a technique to avoid the cyclic prefix insertion, but the residual interferences often exist after the FDE processing according to the channel conditions. The method proposed in this paper suppresses the residual interferences by applying a coherent averaging to the FDE outputs and improve the equalization performances. Computer simulation shows the effect of the proposed technique over the multipath channels.

A novel phase and frequency navigator for proton magnetic resonance spectroscopy using water-suppression cycling.

Magnetic resonance spectroscopy is sensitive to movements, in part, because of motion-induced phase and frequency variations that lead to incoherent averaging. For in vivo proton magnetic resonance spectroscopy, the unsuppressed or under-suppressed water signal can be used to restore coherent averaging; however, this approach results in baseline distortions due to the large water peak. Therefore, a novel water-suppression cycling scheme was developed that alternates between positive and negative residual water signal. Using the residual water signal, the method allows for shot-to-shot phase and frequency correction of individual free induction decays and restoration of signal losses due to incoherent averaging, yet near-complete elimination of residual water. It is demonstrated that the residual water signal can be used to restore metabolite peaks in a brain spectrum from a subject who performed intentional head movements. The ability to correct phase and frequency fluctuations during subject motion is vital for use with adaptive motion correction approaches that ensure proper voxel positioning during head movements.