Showing papers on "Noise (signal processing) published in 1986"

An Adaptive Detection Algorithm

Abstract: A general problem of signal detection in a background of unknown Gaussian noise is addressed, using the techniques of statistical hypothesis testing. Signal presence is sought in one data vector, and another independent set of signal-free data vectors is available which share the unknown covariance matrix of the noise in the former vector. A likelihood ratio decision rule is derived and its performance evaluated in both the noise-only and signal-plus-noise cases.

Exact maximum likelihood parameter estimation of superimposed exponential signals in noise

Abstract: A unified framework for the exact maximum likelihood estimation of the parameters of superimposed exponential signals in noise, encompassing both the time series and the array problems, is presented. An exact expression for the ML criterion is derived in terms of the linear prediction polynomial of the signal, and an iterative algorithm for the maximization of this criterion is presented. The algorithm is equally applicable in the case of signal coherence in the array problem. Simulation shows the estimator to be capable of providing more accurate frequency estimates than currently existing techniques. The algorithm is similar to those independently derived by Kumaresan et al. In addition to its practical value, the present formulation is used to interpret previous methods such as Prony's, Pisarenko's, and modifications thereof.

Position measurement with a resolution and noise‐limited instrument

Abstract: A common problem in experimental data analysis is to locate the position of a signal to an accuracy which is substantially less than the actual signal width. By applying maximum likelihood estimation to this problem, this paper derives theoretical limits on the ability to locate signal position. The limiting error in position measurement is shown to be a simple function of the instrument resolution, the density of sample points, and the signal‐to‐noise ratio of the data. An interesting conclusion is that position information on a much finer scale than the minimum instrument sampling interval is contained in data of modest signal‐to‐noise ratio. The common procedure of excluding the portion of the data lying below an amplitude threshold to guard against background fluctuations is incorporated in the maximum likelihood analysis. It is shown that selection of the optimum amplitude threshold level depends on the type of noise present in the data, and can be an important factor in position accuracy. The analytical results exhibit close agreement with Monte Carlo simulations of position accuracy in the presence of noise.

Use of random noise for on‐line transducer modeling in an adaptive active attenuation system

Abstract: Active sound attenuation systems may be described using a system identification framework in which an adaptive filter is used to model the performance of an unknown acoustical plant. An error signal may be obtained from a location following an acoustical summing junction where the undesired noise is combined with the output of a secondary sound source. In order for the model output to properly converge to a value that will minimize the error signal, it is frequently necessary to determine the transfer function of the secondary sound source and the path to the error signal measurement. Since these transfer functions are continuously changing in a real system, it is desirable to perform continuous on‐line modeling of the output transducer and error path. In this paper, the use of an auxiliary random noise generator for this modeling is described. Based on a Galois sequence, this technique is easy to implement, provides continuous on‐line modeling, and has minimal effect on the final value of the error signal.

Adaptive microphone-array system for noise reduction

Abstract: This paper introduces a new adaptive microphone-array system for noise reduction (AMNOR system). It is first shown that there exists a tradeoff relationship between reducing the output noise power and reducing the frequency response degradation of a microphone-array to a desired signal. It is then shown that this tradeoff can be controlled by the introduction of a fictitious desired signal. A new optimization criterion is presented which minimizes the output noise power while maintaining the frequency response degradation below some pre-determined value (AMNOR criterion). AMNOR determines an optimal noise reduction filter based on this criterion by controlling the tradeoff utilizing the fictitious desired signal. Experiments on noise reduction processing were carried out in a room with a 0.4-s reverberation time. The superiority of the AMNOR criterion over conventional LMS and constrained LMS criteria for reducing noise in speech signals was confirmed in subjective preference tests. The AMNOR system improved the SNR by more than 15 dB in the 300-3200 Hz range.

Adaptive beamforming with the generalized sidelobe canceller in the presence of array imperfections

Abstract: Antenna designers often employ linearly constrained adaptive beamforming as an antijamming measure. With minimal a priori knowledge of the signal environment, this technique nulls out jammers while simultaneously preserving the quality of the main lobe so that a friendly look-direction signal can be received with unity gain. Unfortunately, in the absence of special strategies, linearly constrained adaptive beamforming is hypersensitive to array imperfections when the input signal-to-noise ratio exceeds a certain threshold. This hypersensitivity manifests itself as a nailing of the friendly signal as if it were a jammer. Luckily, the signal nulling problem can be easily remedied by artificial receiver noise injection. A particularly simple and general structure for linearly constrained adaptive beamforming was proposed during the 1970's, and is known as the generalized sidelobe canceller. A detailed analysis of the generalized sidelobe canceller in the presence of array imperfections is discussed, and two new artificial receiver noise injection algorithms are proposed. Computer simulations are included to demonstrate that use of these new algorithms alleviates the signal nailing problem without seriously compromising jammer nulling. For the special case of the Capon maximum-likelihood beamformer, simple approximations are presented for: 1) the Wiener output signal-to-interference-plus-noise ratio ( SINR_{0}\astr ), 2) the antenna element error variance that causes a 3 dB loss of SINR_{0}\astr from its value for an ideal array, and 3) the optimal artificial receiver noise that maximizes SINR_{0}\astr .

Quantitation in positron emission computed tomography : 7. A technique to reduce noise in accidental coincidence measurements and coincidence efficiency calibration

Abstract: A method of processing accidental coincidence events (AC) and detector efficiency (DE) calibration data, which reduces the statistical noise in these measurements, and, consequently, reduces the noise in positron emission tomographic images using the technique, is described. The technique uses the fact that, in these measurements with N detectors in coincidence with N other detectors, N2 values of ACs or DEs are measured. However, these values are composed of only 2N components, which are either singles rates or individual DEs. The full set of data is used to implicitly solve for these values and the individual ACs or DEs recalculated with an improvement in statistical error equivalent to an N2/(2N + 1) increase in accumulated events for the case of a uniform distribution. This result was verified experimentally.

Nonlinear mean filters in image processing

Abstract: The use of nonlinear means in image processing is introduced. The properties of these means in the presence of different types of noise are investigated. It is shown that nonlinear filters based on these means behave well for both additive and impulse noise. Their performance in the presence of signal dependent noise is satisfactory. They preserve the edges better than linear filters, and they reject the noise better than median filters.

Adaptive noise suppressor

Abstract: An adaptive noise suppressor for providing noise filtered signals. The noise suppression device employs a vector gain μ for the weights of the filter wherein the vector μ is selected for each frequency bin to be inversely proportional to the power spectrum. A projection operator is utilized to remove the effects of circular convolution to produce a linear convolution result wherein the weights are readjusted in a manner to minimize the difference between the input signal and the filter output signal, thereby minimizing the error signal to produce a noise suppressed signal in the filtered output. A frequency suppression device utilizes the same principles of the vector μ and projection operator, but the output is taken from the error output of the filter.

On the performance of signal-subspace processing-- Part I: Narrow-band systems

Abstract: This paper presents an analytical evaluation of detection (determination of the number of sources) and estimation performances of narrow-band signal-subspace processing for multiple-source direction finding. The probabilities of underestimating and overestimating the number of sources are derived, under asymptotic conditions and around the threshold regions, in terms of the choice of a penalty function and signal, noise, and array parameters for the cases of at most two closely spaced sources in the spatially white noise. A scalar measure is introduced for the evaluation of the quality of the estimated signal subspace. Based on the statistics of this measure, performance thresholds are demonstrated for the signal-to-noise ratio, angle separation, and correlation between two equipowered sources.

An adaptive IIR structure for sinusoidal enhancement, frequency estimation, and detection

Abstract: An adaptive IIR structure for processing a sinusoidal signal in broad-band noise is introduced. The structure contains three adaptive processors, each of which is computationally very simple. Useful features of the structure include enhancement, frequency estimation, and detection.

Transformer coupled pard bucker for DC power supplies

Abstract: A noise reduction circuit for a DC power supply in which the input of a high pass filter is coupled to the output circuit of the supply so as to receive a noise signal, the output of the high pass filter is coupled to the primary winding of a transformer via an amplifier, and the secondary winding of the transformer is coupled to the output circuit of the supply so as to reduce the noise therein.

Attenuation of Communication Signals on Residential and Commercial Intrabuilding Power-Distribution Circuits

Abstract: The use of electric-power-distribution circuits for intrabuilding communications is ol continued and growing interest. The purpose of this paper is to present intrabuilding signal attenuation measurements taken from five different buildings. The measurements cover the range 20-240 kHz and include transmissions across power phases. The measurements complement earlier measurements by others of power-line impedance and noise. Impedance, attenuation, and noise characterize any communication channel and are needed for design of communication signaling formats, error-control codes, and communication protocols. Except over short distances, attenuation normally exceeds 20 dB, and can be much higher. The attenuation which occurs when the transmitter and receiver use different power-line phases is not always larger than when both are on the same phase. Narrow-band frequency-selective fades can occur and change as network loading changes, and can also exhibit periodic time dependence. Loading, which is time varying, greatly affects signal attenuation between network nodes. The results clearly indicate that power-line signal attenuation is highly variable and unpredictable, is variable with communication signal frequency, and is not easily modeled mathematically. The implications of our results for intrabuilding communications on power-distribution circuits are discussed.

A Kalman filtering approach to short-time Fourier analysis

Abstract: The problem of estimating time-varying harmonic components of a signal measured in noise is considered. The approach used is via state estimation. Two methods are proposed, one involving pole-placement of a state observer, the other using quadratic optimization techniques. The result is the development of a new class of filters, akin to recursive frequency-sampling filters, for inclusion in a parallel bank to produce sliding harmonic estimates. Kalman filtering theory is applied to effect the good performance in noise, and the class of filters is parameterized by the design tradeoff between noise rejection and convergence rate. These filters can be seen as generalizing the DFT.

Adaptive filters suitable for real-time spectral analysis

Abstract: Some new cascade structures for adaptive filters are presented. They are especially suitable for real-time applications. Since the new structures are intended to be realized using single chip DSP IC's or single chip custom VLSI circuits the requirements for memory and divisions are minimized. The new structures are based on state-variable biquads that in addition to having good SNR's and low sensitivities (for fixed-point implementations) can also have their resonant frequencies and Q -factors independently tuned. The special cass of using the adaptive filters for tracking sinusoids corrupted by noise and for formant based speech compression are described in detail.

The Nth-root stack; theory, applications, and examples

Abstract: Multichannel geophysical data are usually stacked by calculating the average of the observations on all channels. In the Nth-root stack, the average of the Nth root of each observation is raised to the Nth power, with the signs of the observations and average maintained. When N = 1, the process is identical to conventional linear stacking or averaging. Nth-root stacking has been applied in the processing of seismic refraction and teleseismic array data. In some experiments and certain applications it is inferior to linear stacking, but in others it is superior. Although the variance for an Nth-root stack is typically less than for a linear stack, the mean square error is larger, because of signal attenuation. The fractional amount by which the signal is attenuated depends in a complicated way on the number of data channels, the order (N) of the stack, the signal-to-noise ratio, and the noise distribution. Because the signal-to-noise ratio varies across a wavelet, peaking where the signal is greatest and approaching zero at the zero-crossing points, the attenuation of the signal varies across a wavelet, thereby producing signal distortion. The main visual effect of the distortion is a sharpening of the legs of the wavelet. However, the attenuation of the signal is accompanied by a much greater attenuation of the background noise, leading to a significant contrast enhancement. It is this sharpening of the signal, accompanied by the contrast enhancement, that makes the technique powerful in beam-steering applications of array data. For large values of N, the attenuation of the signal with low signal-to-noise ratios ultimately leads to its destruction. Nth-root stacking is therefore particularly powerful in applications where signal sharpening and contrast enhancement are important but signal distortion is not.

An Edge Gradient Enhancing Adaptive Order Statistic Filter

Abstract: We consider an adaptive order statistic (OS) filter that can enhance gradients of edges while suppressing impulsive and some nonimpulsive noise components. In particular, comparison and selection (CS) filters are introduced, in which the output is determined by comparing the sample mean and median values inside each window. It is shown theoretically that CS filters can enhance gradients of a variety of edges including noisy blurred ones. Some root properties of CS filters are also shown. Finally, experimental results are presented to illustrate the performance characteristics of these filters.

Image pickup device

Abstract: PURPOSE:To improve the quality of a displayed video by providing a reference zero-level correction circuit to the pre-stage of a processing circuit part and preventing the circuit from being clamped to an erroneous reference-zero-level. CONSTITUTION:A video signal AS conducted from an image pickup element 1 to the reference-zero-level correction circuit 10 flows through a switch 11 during a horizontal scanning period, and is supplied to a video amplification circuit 5. The switch 11 comes in a cut-off state during the blanking period of the video signal AS, and a signal at the reference-zero-level position during the blanking period is conducted to a correction circuit main body 12, and the DC level at a prescribed position is sampled by a switch 13. The signal is smoothed by a smoothing capacitor 15 and supplied to the video amplification circuit 15 through a switch 14, and the DC level at the reference-zero-level position of the video signal AS is substituted. Thus a video signal AS' including no level-fluctured component at the reference-zero-level position is supplied to the processing circuit part 7. As a result, a level varied due to noise, etc. is not erroneously clamped.

Edge Detectors Based on Nonlinear Filters

Abstract: A class of edge detectors is proposed which is obtained from the difference of the outputs of two nonlinear filters. The nonlinear filters used are based on nonlinear means (which contain homomorphic filters) or order statistic (which contain median filters). The performance of these edge detectors in the presence of noise is evaluated and is compared to the performance of well established edge detectors. Their computational requirements are described and some examples are presented.

Nonlinear filtering of one-dimensional diffusions in the case of a high signal-to-noise ratio

Abstract: In this paper, we are concerned with the asymptotic nonlinear filtering of one-dimensional diffusions as the observation noise tends to zero. The intensity of the signal noise may be normal, small or large. We derive evaluations of the conditional moments and obtain one- and two-dimensional approximate filters. We give upper bounds for the approximation errors and compare these filters with some classical suboptimal filters.

Noise updating repeated Wiener filter and other adaptive noise smoothing filters using local image statistics.

Abstract: We consider the restoration of images degraded by a class of signal-uncorrelated noise, which is possibly signal-dependent. Some adaptive noise smoothing filters, which assume a nonstationary mean, nonstationary variance image model implicitly or explicitly, are reviewed, and their performances are compared by the mean-squares errors (MSES) and by the human subjective judgment. We also present a new noise smoothing technique which is called the noise updating repeated Wiener (NURW) filter. Explicit noise variance updating formulas are derived for the NURW filter. The performance is improved both in the MSE sense and in the vicinity of edges by subjective observation.

Passive infrared intrusion detector employing correlation analysis

Abstract: For reducing the susceptibility to false alarms and for increasing the detection probability of a passive infrared detector, the actual signals obtained from a first sensor element are continuously compared in a correlator with reference or set signals stored in a read-only memory and/or with the actual signals obtained from a second sensor element monitoring the near region. The correlator delivers an output signal which corresponds to the correlation of both signals which are compared with one another. An alarm signal is triggered when the correlation exceeds a predetermined value, for instance 0.7, and the amplitude has reached a predetermined threshold. The infrared detector affords high security against giving of false alarms and a high detection probability, even in the presence of signals possessing a great amount of noise, but also delivers an alarm signal in the event the detector is attempted to be sabotaged, for instance by covering the inlet optical system.

Theory and implementation of a Raman active fiber delay line

Abstract: In an optical delay line made of a single-mode reentrant fiber loop, Raman amplification is used to compensate for recirculating signal losses. Concurrent Stokes noise amplification limits the system performances. A theoretical model shows that the signal-to-noise ratio decays as the reciprocal of the number of signal recirculations. Experimental results obtained with a 760-m-long fiber loop operated at \lambda = 1.12 \mu m are presented. A new pump modulation technique resulting in improved output signal stability is reported whereupon optical delays up to 3 ms were achieved.

An analysis of noise propagation in computed T2, pseudodensity, and synthetic spin-echo images.

Abstract: Methods are reviewed for estimating the transverse relaxation time T2 and the pseudodensity (PD) from spin-echo measurements acquired at an arbitrary set of echo times [TEi]. Least-squares fitting is applied to the logarithmically processed signals for the case in which the weights are proportional to the inverse of the logarithmically transformed signal variances (the minimum variance case). General formulas are derived for the estimated noise levels in the PD and T2 estimates due to the propagation of uncertainties in the original measurements. It is shown that the T2 and PD estimates are anticorrelated. Additionally, an expression is derived for the variance in a synthetic spin-echo signal subsequently formed from the PD and T2 estimates. It is shown that under many circumstances a signal synthesized at some echo time can have a signal-to-noise ratio superior to that in a signal directly acquired at that time. Experimental measurements made on phantoms match the theoretical predictions to a high degree.

Method and apparatus for determining his-purkinje activity

Abstract: An apparatus and method for detecting low level bioelectric signals on the surface of a patient. The bioelectric signals are enhanced by filtering out noise through a particular adaptive filtering technique. In detecting His signals at the chest of a patient, surface ECG's are acquired at a plurality of external locations, the acquired data is digitized and stored. One of the ECG signals is selected as a reference channel and the remaining ECG signals are used as input channels. With the use of a feedback coefficient, each data point of interest in each cycle is adaptively filtered to remove the noise and the filtered signal is displayed. The adaptive filtering involves performing two pre-updates of a weight matrix associated with each sample point of each input channel based on the measured samples before and after a sample point, calculating an output signal based on the weight matrix and the input channel, and updating the weight matrices based on the calculated output signal.

Auditory stimulation using cw and pulsed signals

Abstract: An improvement in noise susceptibility is realized in auditory stimulation of the deaf by electrical signals. At least one analog electrical signal is applied to implanted electrodes in a patient, and at least one pulsatile signal is applied to implanted electrodes. The analog signal represents a speech signal, and the pulsatile signal provides specific speech features such as formant frequency and pitch frequency.

Switched-capacitor high-Q bandpass filters for IF applications

Abstract: Experimental results for a sixth-order switched-capacitor bandpass filter with a selectivity Q of 55 at a center frequency of 3.1 MHz are presented. A simple noise analysis of active bandpass filters composed of coupled identical resonators is introduced to explain the dynamic range reduction in high-Q active filters resulting from loose high-Q couplings between resonators. Theoretical predictions of noise in coupled resonator-type bandpass filters agree well with measured results. The prototype chip occupies 2 mm/SUP 2/ and dissipates 45 mW with a single 5-V supply.

A recursive estimation algorithm using selective updating for spectral analysis and adaptive signal processing

Abstract: This correspondence presents a recursive estimation algorithm which, unlike conventional ones, updates the estimates only when a sufficient improvement can be obtained. With a bounded noise, assumption, the resulting sequence of estimates is a sequence of convex sets (ellipsoids) in the parameter space. For the cases studied, the algorithm used less than 20 percent of the data to update the estimates and still acquired very good accuracy for spectral estimation.