Showing papers on "Signal-to-noise ratio published in 1984"

Estimation of QRS Complex Power Spectra for Design of a QRS Filter

Abstract: We present power spectral analysis of ECG waveforms as well as isolated QRS complexes and episodes of noise and artifact. The power spectral analysis shows that the QRS complex could be separated from other interfering signals. A bandpass filter that maximizes the signal (QRS complex)-to-noise (T-waves, 60 Hz, EMG, etc.) ratio would be of use in many ECG monitoring instruments. We calculate the coherence function and, from that, the signal-to-noise ratio. Upon carrying out this analysis on experimentaly obtained ECG data, we observe that a bandpass filter with a center frequency of 17 Hz and a Q of 5 yields the best signal-to-noise ratio.

A Unified Approach to Serial Search Spread-Spectrum Code Acquisition--Part II: A Matched-Filter Receiver

Abstract: The unified theory developed in Part I [1] is employed here in the analysis of a noncoherent, matched-filter (fast-decision-rate) code acquisition receiver in a direct-sequence spread-spectrum system. The results illustrate the dynamic dependence of the mean acquisition time on system parameters, such as the predetection signal-to-noise ratio (SNR), the decision threshold settings, and the ratio of the decision rate to the code rate.

A signal-to-noise calibration procedure for NMR imaging systems

Abstract: A nuclear magnetic resonance (NMR) imaging system signal-to-noise calibration technique based on an NMR projection of distilled water in a cylindrical bottle is proposed. This measurement can characterize any arrangement of rf coils in any magnetic field as signal to noise per ml times root Hz. Inductive losses in a typical patient must be included in the calibration, and such losses can be simulated in a particular system by an externally attached resistor(s) appropriate to that system. Alternatively, an rf inductive damping phantom consisting of a conducting loop of wire containing an appropriate resistor is suggested that can be inserted into any NMR imaging coil to simulate subject Q damping. The same resistor can be used, independent of the details of the coil construction. Furthermore, if the loop inductance is tuned out at each frequency with a series capacitor, then the same loop resistance will serve for all frequencies as a good approximation to human subject damping. This "projection method" signal-to-noise ratio is related to the conventional signal-to-noise ratio measured from a Lorentzian-shaped spectral line as psi P = psi L [2/T2]1/2, where psi stands for signal-to-noise ratio, subscripts P and L stand, respectively, for the projection and "Lorentzian" methods, and T2 is the transverse relaxation time of the spectral line used in the Lorentzian method.

Signal-to-Noise Ratio Advantage of Binaural Hearing Aids and Directional Microphones under Different Levels of Reverberation

Abstract: The signal-to-noise ratio necessary for a constant performance level was determined for normally hearing and hearing-impaired subjects under three levels of reverberation (0.3, 0.6, and 1.2 s) with...

A Prony method for noisy data: Choosing the signal components and selecting the order in exponential signal models

Abstract: Prony's method is a simple procedure for determining the values of parameters of a linear combination of exponential functions. Until recently, even the modern variants of this method have performed poorly in the presence of noise. We have discovered improvements to Prony's method which are based on low-rank approximations to data matrices or estimated correlation matrices [6]-[8], [15]-[27], [34]. Here we present a different, often simpler procedure for estimation of the signal parameters in the presence of noise. This procedure has received only limited dissemination [35]. It is very close in form and assumptions to Prony's method. However, in preliminary tests, the performance of the method is close to that of the best available, more complicated, approaches which are based on maximum likelihood or on the use of eigenvector or singular value decompositions.

Optimal estimators for spectral restoration of noisy speech

Abstract: Acoustic noise suppression is treated as a problem of finding the minimum mean square error estimate of the speech spectrum from a noisy version. This estimate equals the expected value of its conditional distribution given the noisy spectral value, the mean noise power and the mean speech power. It is shown that speech is not Gaussian. This results in an optimal estimate which is a non-linear function of the spectral magnitude. This function differs from the Wiener filter, especially at high instantaneous signal-to-noise ratios. Since both speech and Gaussian noise have a uniform phase distribution, the optimal estimator of the phase equals the noisy phase. The paper describes how the estimator can be calculated directly from noise-free speech. It describes how to find the optimal estimator for the complex spectrum, the magnitude, the squared magnitude, the log magnitude, and the root-magnitude spectra. Results for a speaker dependent connected digit speech recognition task with a base error rate of 1.6%, show that preprocessing the noisy unknown speech with a 10 dB signal-to-noise ratio reduces the error rate from 42% to 10%. If the template data are also preprocessed in the same way, the error rate reduces to 2.1%, thus recovering 99% of the recognition performance lost due to noise.

Accurate frequency estimation at low signal-to-noise ratio

Abstract: A frequency estimator for sinusoids in white noise is described. Convergence results are obtained for the single sinusoid case and a simulation described for the multiple sinusoid case. The estimator is shown to be capable of providing accurate frequency estimates at lower SNR's than currently existing techniques. Furthermore, the simplicity of the algorithm lends itself to a simple and efficient implementation.

On errors of fit and accuracy in matching synthetic seismograms and seismic traces

Abstract: A synthetic seismogram that closely resembles a seismic trace recorded at a well may not be at all reliable for, say, stratigraphic interpretation around the well. The most accurate synthetic seismogram is, in general, not the one that displays the smallest errors of fit to the trace but the one that best estimates the noise on the trace. If the match is confined to a short interval of interest or if the seismic reflection wavelet is allowed to be unduly long, there is considerable danger of forcing a spurious fit that treats the noise on the trace as part of the seismic reflection signal instead of making a genuine match with the signal itself. This paper outlines tests that allow an objective and quantitative evaluation of the accuracy of any match and illustrates their application with practical examples. The accuracy of estimation is summarized by the normalized mean square error (NMSE) in the estimated reflection signal, which is shown to be (/n)(PN/PS) where PS/PN is the signal-to-noise power ratio and n is the spectral smoothing factor. That is, the accuracy varies directly with the ratio of the power in the signal (taken to be the synthetic) to that in the noise on the seismic trace, and the smoothing acts to improve the accuracy of the predicted signal. The construction of confidence intervals for the NMSE is discussed. Guidelines for the choice of the spectral smoothing factor n are given. The variation of wavelet shape due to different realizations of the noise component is illustrated, and the use of confidence intervals on wavelet phase is recommended. Tests are described for examining the normality and stationarity of the errors of fit and their independence of the estimated reflection signal.

Signal Processing for Proportional Myoelectric Control

Abstract: Proportional myoelectric control of powered prostheses requires the estimation of a time-varying control signal from the patient's myoelectric signal. Since the myoelectric signal is a zero-mean stochastic process, a nonlinearity is a necessary element of the estimator. Typically, a full-wave rectifier is used for this nonlinearity, followed by a low-pass filter to complete the estimation of the control signal. In this work, it is proposed to use a logarithmic nonlinearity, followed by a linear minimum mean-square error estimator. The logarithmic nonlinearity maps the myoelectric signal into an additive control signal-plus-noise domain in which the Kalman filter is employed to estimate the control signal. The theoretical performance of this estimator is obtained and verified by experiments.

Biofeedback method and apparatus

Abstract: The new biofeedback technique permits simultaneous, preferably redundant visual and auditory presentation of any intrinsically motivating stimuli together with continous information pertaining to the physiological parameter to be controlled. Essentially, it varies the signal to noise ratio (S/N) of an audio or video signal as a function of any physiological parameter or combination of several parameters. That is, intrinsically motivating stimuli, visual and auditory, are presented through a color TV set; image and sound are initially masked by white noise, set to a level just above perception (minimum signal and maximum noise). As the experimental subject changes a certain physiological parameter, image and sound become clearer if the change occurs in the desired direction. The video signal remains synchronized at any noise level. The final S/N ratio has been utilized as an index of motivation in an experiment to evaluate the efficiency of the new technique.

Performance Analysis And Size Optimization Of Focal Planes For Point-Source Tracking Algorithm Applications

Abstract: A number of applications require the precise tracking or position estimation of an object unresolved in the system optics. This paper evaluates several one-dimensional interpolation algorithms (odd N-point centroids, N = 3, 5, 7, 9, and three-point and five-point quadratic curve fits) designed to make these estimates to subpixel accuracy. Analytic, Monte Carlo, and experimental results are presented. The tracking sensor examined was a scanning linear array of infrared detectors assumed to be background-limited. The detector size and physical spacing were varied parametrically, with realistic fabrication constraints, to determine the relative performance and to obtain the optimum configuration. The optics blur spot was assumed Gaussian. The sources of error considered to affect the algorithm performance were the systematic algorithm bias, the random noise, and the postcalibration residual detector responsivity nonuniformities. Track accuracy improves with signal-to-noise ratio (SNR), until limited by algorithm inaccuracies or focal-plane nonuniformity. Among the algorithms tested, the three-point centroid performs best, provided that systematic algorithm bias is corrected. An experimental infrared tracking focal plane, used in a tracker simulation, closely confirmed the analysis. With the three-point algorithms, an experimental accuracy to smaller than 1/100 a detector (<1/250 a blur spot) was obtained at high signal-to-noise ratios.

Robust Smoothing Applied to White Noise and Single Outlier Contaminated Raman Spectra

Abstract: There are several smoothing procedures for spectral data which are affected by occasionally occurring outliers. Most of the known methods are based on local averages (or fits) of the spectral data. We introduce here an outlier-insensitive, robust smoothing method which rejects the influence of huge noise spikes. The proposed smoothing algorithm can be tuned by two parameters. The first corresponds to the signal-to-noise ratio, the second to the halfwidths of the spectral bands. We apply this new technique to several spectra and prove the advantages of our method of identifying peaks and baselines in Raman spectroscopy.

Detection of multiple sinusoids using an adaptive cascaded structure

Abstract: The purpose of this paper is to present a simple adaptive algorithm for detecting and tracking a sinusoid in broadband noise, while at the same time improving its signal-to-noise ratio (SNR).

The high-resolution spectrum estimator&#8212;A subjective entity

Abstract: It is shown by example that the attribute of high resolution for a spectrum estimator can be a subjective one The particular spectrum estimator considered is the MUSIC algorithm, although the observations are valid for any spectrum estimator The main point is that visual examination of spectra is not a scientifically valid means of assessing resolution

On eigenvalues, SINR, and element patterns in adaptive arrays

Abstract: A simple relationship between the output signal-to-interference-plus-noise ratio (SINR) of an adaptive array and the eigenvalues of the associate signal covariance matrix is pointed out. For two simple cases involving continuous wave (CW) signals, it is shown that the eigenvalue associated with the desired signal is equal to the SINR plus one. This relationship is useful for understanding the effects of element patterns and spacings on eigenvalue behavior in adaptive arrays.

On the estimation of magnetotelluric response functions using the singular value decomposition

Abstract: Summary Rigorous methods for computing magnetotelluric response function estimates and their variances from electromagnetic field measurements using the singular value decomposition (SVD) are presented. The relative noise level between the electric and magnetic field components is treated as a free variable, and is shown profoundly to affect both the response function estimates and their variances. In general, the variances decrease to a minimum as the field components share noise more equally. A statistical parameter for checking the validity of the usual magnetotelluric assumptions (two-dimensional conductivity structure and homogeneous source fields) as a function of frequency is developed and applied to the estimation of the ratio of electric and magnetic field noise in data. The method is illustrated using both synthetic and real magnetotelluric data. Results from a seafloor experiment in the NW Pacific show that the response functions obtained primarily from the east electric and north magnetic fields are better determined than the conjugate function, reflecting higher field coherences, but yields no significant statistical difference between the principal components of the response tensor. The ratio of magnetic to electric field noise appears to increase at frequencies below 0.5 cph, and evidence for source field complications, as suggested by high vertical to horizontal magnetic field coherence, is widespread and may reflect ocean-generated electromagnetic fields.

An improved eigenvector beamformer

Abstract: Most techniques for computing beamformer tap weights do so by maximizing the overall signal-to-noise ratio at the system output, where noise includes both thermal noise and directional interference. This is the optimal solution if the two noise sources count equally. However, there do exist scenarios where directional interference is more harmful to system performance. For this reason, the authors introduced a new beam-former based on eigenvector techniques[1] which is able to exactly null interference even when thermal noise is present. Unfortunately, however, the new method can also cause signal cancellation, depending on the geometry of the interference. This cancellation can be reduced by introducing additional eigenvectors in the tap weight solution. We develop a criterion for choosing these additional vectors which allows the user to set the maximum tolerable signal cancellation. Given this signal cancellation constraint, the directional interference power is minimized. Simulation results are presented which demonstrate the modified eigenvector beamformer. We also comment on the extension of the method to wide-band signals.

Some Theoretic Results on a Digital EMG Signal Processor

Abstract: As is well known, a general EMG signal processing scheme includes a prewhitening filter, a v-order detector, a smoothing filter, and a relinearizer. In this paper, a theoretical analysis of such a scheme is carried out, including a detector characteristic which presents a logarithmic behavior.

Delay estimation by expected value

Abstract: The estimation of time delay between narrowband signals is discussed. A minimum mean square error (MMSE) estimator is used that utilizes the maximum likelihood (ML) window derived by Knapp and Carter in obtaining the required conditional probability density function from which the delay estimate is calculated. The results of simulations using a narrowband signal are presented which evaluate and compare the mean square error of the MMSE and ML processors. The MMSE estimator shows improvement over the ML estimator, particularly in regions below the threshold signal-to-noise ratio. Conditions for application of the MMSE processor are discussed as well as some important considerations for its implementation.

Space diversity receiver

Abstract: In a space diversity receiver for receiving broadcast signals and having first and second antennas coupled to first and second receiving circuits, respectively, for supplying first and second output signals therefrom to a switching circuit which normally selectively supplies the one of the output signals detected to have a superior or better signal to noise ratio; a judging circuit is provided for comparing the better signal to noise ratio of an output signal with a predetermined value and for producing a stop or inhibiting signal when the signal to noise ratio is lower than the predetermined value, and such inhibiting signal temporarily causes the switching circuit to stop switching between the output signals and to continuously supply one of the output signals.

Detection Loss of the Sample Matrix Inversion Technique

Abstract: The sample matrix inversion (SMI) technique is used for Doppler and/or array processing. Previous analysis of the technique has been in terms of signal-to-interference plus noise ratio (SINR). For Gaussian statistics, this performance measure gives the same loss values as does a probability of detection analysis for linear-time invariant systems. It is often somewhat less valid for nonlinear or time variant systems. As SMI is a nonlinear technique, a probability of detection analysis has been performed. It is shown that the detection loss is larger than that computed by the SINR measure. It is also shown that though the loss predicted by the SINR measure only depends upon the number of measurements used to estimate the covariance matrix, the detection loss depends upon the false alarm probability and the number of adaptable elements in addition to the number of measurements.

Maximum heterodyne efficiency of optical heterodyne detection in the presence of background radiation

Abstract: Maximum heterodyne efficiency is obtained for an optical heterodyne detection system in the presence of background radiation. When the local oscillator (LO) power is limited, the signal-to-noise ratio in the output is degraded from that of quantum-noise-limited detection by the background radiation noise. To reduce it, an aperture is used in front of the detector. The optimum incidence conditions of the signal and the corresponding maximum heterodyne efficiency are obtained numerically assuming that the signal and the LO fields are determinable and have Gaussian amplitude distributions. The spontaneous emission from the laser amplifier located just in front of the system is taken into account as the background radiation.

Signal-To-Noise Measurements For A Screen-Film System

Abstract: The signal-to-noise ratio associated with recording Q quanta may be defined in terms of a lesser number of noise-equivalent quanta (NEQ). Measurements are presented here for a screen-film system as used to record x-rays, and the results are expressed in three-dimen-sional form by mapping out the NEQ surface as a function of exposure and spatial frequency.

Modeling of Accidental Coincidences in Both Conventional and Time-of-Flight Positron-Emission Tomography

Abstract: Mathematical predictions [1,2,3] of the improvement in image signal-to-noise ratio that results when time-of-flight information is used in positron-emission tomography (PET) are smaller than the improvement observed experimentally [8]. It has been conjectured [8] that the additional performance gain is due to the way in which accidental coincidences are suppressed by the time-of-flight data-acquisition and reconstruction processes.

Limits to signal-to-noise improvement by FID averaging in NMR imaging

Abstract: The authors studied the improvement of signal-to-noise ratio (SNR) in NMR images by free induction decay (FID) averaging. They found that as the number of FIDs averaged increases, a region is reached where the image SNR levels off asymptotically. A theoretical explanation for this behaviour is offered. Agreement between experimental results and theoretical prediction is excellent. It is also pointed out that the exact location of the point at which further averaging does not pay-off is dependent on the individual NMR imaging system used.

Noise reduction methods for hybrid subtraction

Abstract: In digital subtraction angiography, hybrid subtraction provides selective vessel images free of soft-tissue motion artifacts but with a lower signal-to-noise ratio (SNR) than temporal subtraction images. An image processing method called measurement-dependent filtering has been developed to enhance the SNR of hybrid images without losing resolution or selectivity. Linear combinations of four images consisting of a pre- and postcontrast dual-energy measurement pair form both the hybrid image and a lower noise but less selective vessel image. The noise-reduced image is derived by combining the low-frequency components of the hybrid image with the high-frequency components of the lower noise image in a variety of ways. The results of the filtering method, when tested on both phantom and clinical data, display images with about the same degree of conspicuity as the hybrid image and a SNR approaching that of the temporal image.

Reaction time to a tone in noise as a function of the signal-to-noise ratio and tone level

Abstract: Reaction time to the onset of a 1-kHz tone against a background of continuous noise was investigated. Results showed reaction time to decrease with increasing tonal level, even when the signal-to-noise ratio was held constant, implying that Weber’s law does not hold for reaction time to a tone in noise. When the reaction times were plotted against the loudness of the tone, determined independently in a second experiment, no simple relationship emerged, contrary to the hypothesis that reaction time to a sound is a simple function of its loudness. It is concluded that reaction time processes differ from the processes involved in loudness discrimination or in signal detection.