Showing papers on "Noise (signal processing) published in 1999"

Adaptive reconstruction of phased array NMR imagery

Abstract: A method to model the NMR signal and/or noise functions as stochastic processes. Locally relevant statistics for the signal and/or noise processes are derived directly from the set of individual coil images, in the form of array correlation matrices, by averaging individual coil image cross-products over two or more pixel locations. An optimal complex weight vector is computed on the basis of the estimated signal and noise correlation statistics. The weight vector is applied to coherently combine the individual coil images at a single pixel location, at multiple pixel locations, or over the entire image field of view (FOV).

Detecting a stochastic background of gravitational radiation: Signal processing strategies and sensitivities

Abstract: We analyze the signal processing required for the optimal detection of a stochastic background of gravitational radiation using laser interferometric detectors. Starting with basic assumptions about the statistical properties of a stochastic gravity-wave background, we derive expressions for the optimal filter function and signal-to-noise ratio for the cross-correlation of the outputs of two gravity-wave detectors. Sensitivity levels required for detection are then calculated. Issues related to (i) calculating the signal-to-noise ratio for arbitrarily large stochastic backgrounds, (ii) performing the data analysis in the presence of nonstationary detector noise, (iii) combining data from multiple detector pairs to increase the sensitivity of a stochastic background search, (iv) correlating the outputs of 4 or more detectors, and (v) allowing for the possibility of correlated noise in the outputs of two detectors are discussed. We briefly describe a computer simulation that was used to ``experimentally'' verify the theoretical calculations derived in the paper, and which mimics the generation and detection of a simulated stochastic gravity-wave signal in the presence of simulated detector noise. Numerous graphs and tables of numerical data for the five major interferometers (LIGO-WA, LIGO-LA, VIRGO, GEO-600, and TAMA-300) are also given. This information consists of graphs of the noise power spectra, overlap reduction functions, and optimal filter functions; also included are tables of the signal-to-noise ratios and sensitivity levels for cross-correlation measurements between different detector pairs. The treatment given in this paper should be accessible to both theorists involved in data analysis and experimentalists involved in detector design and data acquisition.

Touch confirming touchscreen utilizing plural touch sensors

Abstract: A method and apparatus for discriminating against false touches in a touchscreen system is provided. The system is designed to confirm a touch registered by one touch sensor with another touch sensor, preferably of a different sensor type, prior to acting upon the touch (i.e., sending touch coordinates to the operating system). If the touch registered by the first touch sensor is not confirmed by the second touch sensor, the touch is invalidated. Thus the strengths of one type of sensor are used to overcome the deficiencies of another type of sensor. In one aspect, the secondary touch sensor comprises a force sensor to discriminate between true and false touches on other types of touch sensors, such as contaminants on optical and surface acoustic wave sensors, noise or weak signals on capacitive sensors, etc. The force sensor may be a simple one-element system that merely indicates that a touch has occurred or a multi-element system that can provide confirming or supplementary coordinate data. In another aspect, a capacitive sensor is used to confirm or veto touch data from optical, surface acoustic wave, and force sensors. As is the case with the secondary force sensor, a secondary capacitive sensor may be a simple discrete type or capable of providing touch coordinates in its own right. In a specific embodiment, one in which no touch overlay is used on a CRT monitor, the secondary touch sensor may employ the resistive coating on the surface of the CRT in combination with a current monitoring circuit that measures the amplitude of the electromagnetic noise signal coupled to the resistive coating. In this application when the screen is touched by a grounded object, the detected signal amplitude change exceeds a preset threshold thus indicating a valid touch.

A time-efficient and accurate strain estimation concept for ultrasonic elastography using iterative phase zero estimation

Abstract: In ultrasonic elastography, the exact estimation of temporal displacements between two signals is the key to estimating strain. An algorithm was previously proposed that estimates these displacements using phase differences of the corresponding base-band signals. A major advantage of these algorithms compared with correlation techniques is the computational efficiency. In this paper, an extension of the algorithm is presented that iteratively takes into account the time shifts of the signals to overcome the problems of aliasing and accuracy in the estimation of the phase shift. Thus, it can be proven that the algorithm is equivalent to the search of the maximum of the correlation function. Furthermore, a robust logarithmic compression is proposed that only compresses the envelope of the signal. This compression does not introduce systematic errors and significantly reduces decorrelation noise. The resulting algorithm is a computationally simple and very fast alternative to conventional correlation techniques, and the accuracy of strain images is improved.

A globally convergent frequency estimator

Abstract: Online estimation of the frequency of a sinusoidal signal is a classical problem in systems theory that has many practical applications. In this paper the authors provide a solution to the problem of ensuring a globally convergent estimation. More specifically, they propose a new adaptive notch filter whose dynamic equations exhibit the following remarkable features: 1) all signals are globally bounded and the estimated frequency is asymptotically correct for all initial conditions and all frequency values; 2) the authors obtain a simple tuning procedure for the estimator design parameters, which trades-off the adaptation tracking capabilities with noise sensitivity, ensuring (exponential) stability of the desired orbit; and 3) transient performance is considerably enhanced, even for small or large frequencies, as witnessed by extensive simulations. To reveal some of the stability-instability mechanisms of the existing algorithms and motivate our modifications the authors make appeal to a novel nonlinear (state-dependent) time scaling. The main advantage of working in the new time scale is that they remove the coupling between the parameter update law and the filter itself, decomposing the system into a feedback form where the required modifications to ensure stability become apparent. Even though they limit their attention here to the simplest case of a single constant frequency without noise the algorithm is able to track time-varying frequencies, preserve local stability in the presence of multiple sinusoids, and is robust with respect to noise.

Multilevel signaling for increasing the reach of 10 Gb/s lightwave systems

Abstract: Polybinary, optical amplitude modulated phase shift keying (AM-PSK) polybinary, M-ary amplitude shift keying (ASK), and polyquaternary signaling schemes operating at 10 Gb/s are investigated in 1550-nm lightwave systems operating over standard, single-mode fiber. The premise for exploring these signal types is that they concentrate power at frequencies closer to the optical carrier where phase distortion of the optical field from chromatic dispersion is less severe. Issues such as modulator chirp, optimal level spacing in a 4-ary ASK signal, and phase modulated to amplitude modulated (PM-AM) noise conversion from a nonzero laser linewidth are studied. It is found that higher order polybinary signals do not offer an improvement in dispersion tolerance over a duobinary signal. 4-ary ASK is demonstrated to increase the dispersion-limited distance to 225 km experimentally and 350 km through simulation, but at the expense of a /spl sim/8 dB degradation in receiver sensitivity due to the increased number of levels and the signal dependence of signal-spontaneous beat noise. Furthermore, the linewidth requirement for a 4-ary ASK signal is less than 1 MHz in order to minimize the impact of PM-AM relative intensity noise (RIN) when transmitting over 200-300 km.

The application of chaotic oscillators to weak signal detection

Abstract: In this paper, the authors introduce a signal detection scheme based on the bifurcation behavior of the driven Duffing oscillator. Chaotic systems are sensitive to certain signals and immune to noise at the same time, the properties of which demonstrate their potential application in weak signal detection. Starting from the analysis of the intermittent chaotic motion occurring in the detecting process, they put forward a new frequency-locking principle based on the periodic characteristic of the intermittent chaos. Then, an exposition is made on how to use an array of the oscillators to detect the weak signals of unknown frequency.

Method and apparatus for filtering electrocardiogram (ECG) signals to remove bad cycle information and for use of physiologic signals determined from said filtered ECG signals

Abstract: In using electrogram signals to determine physiologic conditions like ischemia, the bad cardiac cycle information due to noise, axis shifts in the cardiac electrical axis, and the like must be removed if the electrogram signal can be made to be a good indicator. If this is accomplished through the adaptive filtering techniques shown here, the signal can be used to drive a closed loop therapy system responsive to those physiologic conditions discernible from good cardiac cycle electrocardiogram signals.

A comparison of two methods for measuring the signal to noise ratio on MR images

Abstract: The signal to noise ratio (SNR) is one of the important measures of the performance of a magnetic resonance imaging (MRI) system. The object of this study was to compare a single acquisition method, which estimates the noise from background pixels, with a dual acquisition method which estimates the noise from the subtraction of two sequentially acquired images. The dual acquisition method is more exact, but is slower to perform and requires image manipulation. A comparison between the two methods gave a good correlation, and a regression equation of SNRsingle = 1.1 + 0.94 SNRdual. The single acquisition method is therefore appropriate for use in a quality assurance programme, since it is quicker and simpler to perform and is a good indicator of the more exact measure.

GNSS Multipath Mitigation Using Gated and High Resolution Correlator Concepts

Abstract: This paper considers Global Navigation Satellite System (GNSS) receiver signal processing–based methods for mitigating multipath using novel correlator waveform concepts. The “Gated Correlator” approach utilizes blanking of the received signal between code chip transitions. Applying the Gated Correlator to GPS C/A– code yields code and carrier multipath mitigation perfor-mance that surpasses conventional GPS P–code performance. The “High Resolution Correlator” tech-nique approximates the performance of the Gated Corre-lator but can be obtained using multiple correlator outputs from conventional receiver hardware. The multipath performance of these methods is similar to the perfor-mance claimed for other methods reported in the litera-ture. However here a complete derivation for these methods is presented as well as a detailed assessment of the performance of these techniques in the presence of wideband noise.

Time-frequency MUSIC

Abstract: A new method for the estimation of the signal subspace and noise subspace based on time-frequency signal representations is introduced. The proposed approach consists of the joint block-diagonalization (JBD) of a set of spatial time-frequency distribution matrices. Once the signal and noise subspaces are estimated, any subspace based approach, including the multiple signal classification (MUSIC) algorithm, can be applied for direction of arrival (DOA) estimation. Performance of the proposed time-frequency MUSIC (TF-MUSIC) for an impinging chirp signal using three different kernels is numerically evaluated.

Multi-agent pseudo-differential signaling scheme

Abstract: A circuit for reducing the effect of noise on signals. The circuit includes a plurality of information signal lines having a substantially matched routing, and a reference voltage line having a routing substantially matched to the routing of the plurality of information signal lines. The circuit further includes a transmitting agent coupled to the plurality of information signal lines and to the reference voltage signal line, including a noise coupling circuit for coupling noise from the transmitting agent to the reference voltage line.

Model-free functional MRI analysis using Kohonen clustering neural network and fuzzy C-means

Abstract: Conventional model-based or statistical analysis methods for functional MRI (fMRI) suffer from the limitation of the assumed paradigm and biased results. Temporal clustering methods, such as fuzzy clustering, can eliminate these problems but are difficult to find activation occupying a small area, sensitive to noise and initial values, and computationally demanding. To overcome these adversities, a cascade clustering method combining a Kohonen clustering network and fuzzy c means is developed. Receiver operating characteristic (ROC) analysis is used to compare this method with correlation coefficient analysis and t test on a series of testing phantoms. Results show that this method can efficiently and stably identify the actual functional response with typical signal change to noise ratio, from a small activation area occupying only 0.2% of head size, with phase delay, and from other noise sources such as head motion. With the ability of finding activities of small sizes stably, this method can not only identify the functional responses and the active regions more precisely, but also discriminate responses from different signal sources, such as large venous vessels or different types of activation patterns in human studies involving motor cortex activation. Even when the experimental paradigm is unknown in a blind test such that model-based methods are inapplicable, this method can identify the activation patterns and regions correctly.

Do's and don'ts in Fourier analysis of steady-state potentials

Abstract: Fourier analysis is a powerful tool in signal analysis that can be very fruitfully applied to steady-state evoked potentials (flicker ERG, pattern ERG, VEP, etc) However, there are some inherent assumptions in the underlying discrete Fourier transform (DFT) that are not necessarily fulfilled in typical electrophysiological recording and analysis conditions Furthermore, engineering software-packages may be ill-suited and/or may not fully exploit the information of steady-state recordings Specifically: * In the case of steady-state stimulation we know more about the stimulus than in standard textbook situations (exact frequency, phase stability), so 'windowing' and calculation of the 'periodogram' are not necessary * It is mandatory to choose an integer relationship between sampling rate and frame rate when employing a raster-based CRT stimulator * The analysis interval must comprise an exact integer number (eg, 10) of stimulus periods * The choice of the number of stimulus periods per analysis interval needs a wise compromise: A high number increases the frequency resolution, but makes artifact removal difficult; a low number 'spills' noise into the response frequency * There is no need to feel tied to a power-of-two number of data points as required by standard FFT, 'resampling' is an easy and efficient alternative * Proper estimates of noise-corrected Fourier magnitude and statistical significance can be calculated that take into account the non-linear superposition of signal and noise These aspects are developed in an intuitive approach with examples using both simulations and recordings Proper use of Fourier analysis of our electrophysiological records will reduce recording time and/or increase the reliability of physiologic or pathologic interpretations

Reduced-order modeling of time-varying systems

Abstract: We present algorithms for reducing large circuits, described at SPICE-level detail, to much smaller ones with similar input-output behavior. A key feature of our method, called time-varying Pade (TVP), is that it is capable of reducing time-varying linear systems. This enables it to capture frequency-translation and sampling behavior, important in communication subsystems such as mixers and switched-capacitor filters, Krylov-subspace methods are employed in the model reduction process. The macromodels can be generated in SPICE-like or AHDL format, and can be used in both time- and frequency-domain verification tools. We present applications to wireless subsystems, obtaining size reductions and evaluation speedups of orders of magnitude with insignificant loss of accuracy. Extensions of TVP to nonlinear terms and cyclostationary noise are also outlined.

Apparatus and method for noise attenuation in a speech recognition system

Abstract: The noise suppressor utilizes statistical characteristics of the noise signal to attenuate amplitude values of the noisy speech signal that have a probability of containing noise. In one embodiment, the noise suppressor utilizes an attenuation function having a shape determined in part by a noise average and a noise standard deviation. In a further embodiment, the noise suppressor also utilizes an adaptive attenuation coefficient that depends on signal-to-noise conditions in the speech recognition system.

Analog signal processing

Abstract: Signals and Signal Processing. Voltage Amplification. Current-to-Voltage and Voltage-to-Current Conversion. Linear Analog Functions. AC/DC Signal Conversion. Other Nonlinear Analog Functions. Analog Signal Filtering. Analog Signal Switching, Multiplexing and Sampling. Error Analysis and Reduction. Interference and Its Reduction. Noise, Drift and Their Reduction. Appendices. Index.

Non-invasive digital cable test system

Abstract: Method and apparatus for non-invasive testing of digital communications systems. Amplitude measurements are made for multiple frequencies of a multi-frequency communication system, converted to the time domain. An adaptive filter output is matched to the time domain representation to characterize the channel. Impedance mismatches may be precisely located using this technique. An error signal representing a difference between a signal transmitted through the channel and a received signal is estimated and analyzed. The error signal is separated into components corresponding to contributions by wide band noise, residual phase modulation, and residual amplitude modulation. Identification and removal of narrow-band interferers may occur prior to this separation. Bit error rate and system margin computations employ a Monte Carlo simulation of the various error sources. This provides a well refined estimate of bit error rate and system margin.

Oscillatory Spatiotemporal Signal Detection in Climate Studies: A Multiple-Taper Spectral Domain Approach

Abstract: Publisher Summary This chapter introduces a methodology for signal detection and reconstruction of irregular spatiotemporal oscillatory signals—the multiple-taper spectrum estimation method (MTM)–singular-value decomposition (SVD) methodology. This methodology is offered as an alternative technique which avoids most of the problems encountered in traditional techniques and provides an efficient exploratory method for climate signal detection. The associated signal-detection parameter—the local fractional variance spectrum (LFV) spectrum—yields the correct null distribution for a very general class of spatiotemporal climate noise processes and the correct inferences when signals are present. The methodology allows for a faithful reconstruction of the arbitrary spatiotemporal patterns of narrowband signals immersed in spatially correlated noise. The results of the MTM–SVD approach are robust to the temporal and spatial sampling inhomogeneities that are common in actual climate data. Applied to observational climate data, the MTM–SVD analysis yields insight into secular trends, low-frequency, and high-frequency quasi-oscillatory variations in the climate system. The dominant mode of secular variation has been a long-term global warming trend associated with some anomalous atmospheric circulation patterns that show similarity to the modeled response of the climate to increased greenhouse gases.

Identification of digital modulation types using the wavelet transform

Abstract: Automatic identification of the digital modulation type of a signal has found applications in many areas, including electronic warfare, surveillance and threat analysis. This paper studies the use of wavelet transform to distinguish QAM signal, PSK signal and FSK signal. The approach is to use the wavelet transform to extract the transient characteristics in a digital modulation signal, and apply the distinct pattern in wavelet transform domain for simple identification. The relevant statistics for optimum threshold selection are derived under the condition that the input noise is additive white Gaussian. The performance of the identification scheme is investigated through simulations. When the CNR is greater than 5 dB, the percentage of correct identification is about 97% with 50 observation symbols.

ECG noise filtering using wavelets with soft-thresholding methods

Abstract: We analyze algorithms for filtering white gaussian noise and 50 Hz power line noise from ECG signals. We used several wavelets to study their effect and efficiency in the filtering process. To deal with these different kinds of noises we used two distinct soft-thresholding techniques: the Donoho's statistical threshold estimator and a method developed by us. This last method exploits one of the wavelet processing main features: time-frequency relation. The de-noising methods led to good filtering results: noise reduction with only minor change of the ECG waveforms as confirmed by the high correlation values between the processed signal and the original one. These good results are due to a wavelet advantage over classical filtering-time-frequency relation-enabling the possibility of filtering noise in the same frequency band of the ECG signal with minimal interference.

Method and apparatus for enhancing noise-corrupted speech

Abstract: A noise suppression device receives data representative of a noise-corrupted signal which contains a speech signal and a noise signal, divides the received data into data frames, and then passes the data frames through a pre-filter to remove a dc-component and the minimum phase aspect of the noise-corrupted signal. The noise suppression device appends adjacent data frames to eliminate boundary discontinuities, and applies fast Fourier transform to the appended data frames. A voice activity detector of the noise suppression device determines if the noise-corrupted signal contains the speech signal based on components in the time domain and the frequency domain. A smoothed Wiener filter of the noise suppression device filters the data frames in the frequency domain using different sizes of a window based on the existence of the speech signal. Filter coefficients used for Wiener filter are smoothed before filtering. The noise suppression device modifies magnitude of the time domain data based on the voicing information outputted from the voice activity detector.

Towards true crosstalk noise analysis

Abstract: Accurate noise analysis is currently of significant concern to high-performance designs, and the number of signals susceptible to noise effects will certainly increase in smaller process geometries. Our approach uses a combination of temporal and functional information to eliminate false transition combinations and thereby overcome insufficiencies in static noise analysis. A similar idea arises in timing analysis where functional and timing information is used to eliminate false paths. The goal of our work is to develop an algorithm, software tool, and noise analysis flow that provide an accurate and conservative approach to noise analysis. In particular, this paper proposes an approach to identifying a pair of vectors that exercises the maximum crosstalk noise.

A signal-dependent autoregressive channel model

Abstract: A fast and accurate channel model is presented that captures intersymbol interference, signal non-linearities and signal-dependent noise correlation. The noise is modeled as the output of a signal-dependent autoregressive filter. This channel model is well suited for detector designers who desire realistic simulators with short run-times.

Training neural networks with additive noise in the desired signal

Abstract: A global optimization strategy for training adaptive systems such as neural networks and adaptive filters (finite or infinite impulse response) is proposed. Instead of adding random noise to the weights as proposed in the past, additive random noise is injected directly into the desired signal. Experimental results show that this procedure also speeds up greatly the backpropagation algorithm. The method is very easy to implement in practice, preserving the backpropagation algorithm and requiring a single random generator with a monotonically decreasing step size per output channel. Hence, this is an ideal strategy to speed up supervised learning, and avoid local minima entrapment when the noise variance is appropriately scheduled.

Object detection using pulse coupled neural networks

Abstract: Describes an object detection system based on pulse coupled neural networks. The system is designed and implemented to illustrate the power, flexibility and potential the pulse coupled neural networks have in real-time image processing. In the preprocessing stage, a pulse coupled neural network suppresses noise by smoothing the input image. In the segmentation stage, a second pulse coupled neural-network iteratively segments the input image. During each iteration, with the help of a control module, the segmentation network deletes regions that do not satisfy the retention criteria from further processing and produces an improved segmentation of the retained image. In the final stage each group of connected regions that satisfies the detection criteria is identified as an instance of the object of interest.

Theoretical noise reduction limits of the generalized sidelobe canceller (GSC) for speech enhancement

Abstract: We present an analysis of the generalized sidelobe canceller (GSC). It can be shown that the theoretical limits of the noise reduction performance depend only on the auto- and cross-spectral densities of the input signals. Furthermore, we compute the limits of the noise reduction performance for the theoretically determined diffuse noise field, which is an approximation for reverberant rooms. Our results show that the GSC cannot reduce noise further than 1 dB. These results were verified by simulation of reverberant environments. Only in sound-proof rooms with a reverberation time less than 100 ms the GSC performs well.

First-break timing: Arrival onset times by direct correlation

Abstract: In attenuating media, pulse characteristics evolve with propagation distance and saturation or pressure-dependent changes in rock properties. This nonstationarity of the waveform complicates determination of meaningful traveltimes. As a result, depending on the time-picking criteria used, substantially different values of interval velocity can be obtained. This problem is particularly severe in high-frequency laboratory time-of-flight measurements on porous rock. A potentially less ambiguous measure of wave speed is the signal velocity that is calculated using the pulse onset time. Here, a semiautomated method is developed to determine this onset time in high-fidelity, pressure-dependent core measurements. The greatest value of Pearson’s correlation coefficient between segments of observed waveforms near the pulse onset and at an appropriate reference serves as the time determination criterion. Tests of the method on artificial data suggest the signal velocity may be determined to better than 0.3% fori60 dB noise or 1.2% fori37 dB noise. A real data set is tested, comprised of a series of ultrasonic (1 MHz) velocity measurements in microcracked rock to confining pressures of 300 MPa (»45,000 psi). At the lowest confining pressure, where attenuation is greatest, signal onset and more conventionally derived traveltimes differ by more than 4%. This large discrepancy illustrates that care should be exercised when determining velocity in such attenuating materials. Conversely, the consistency of waveform attributes, such as the difference between the onset time and the first peak time or the apparent quality factor, is useful when estimating intrinsic material velocities in low-porosity, microcracked carbonate and metamorphic rocks at high confining pressures.

Signal-to-noise ratio and signal-to-noise efficiency in SMASH imaging.

Abstract: A general theory of signal-to-noise ratio (SNR) in simultaneous acquisition of spatial harmonics (SMASH) imaging is presented, and the predictions of the theory are verified in imaging experiments and in numerical simulations. In a SMASH image, multiple lines of k-space are generated simultaneously through combinations of magnetic resonance signals in a radiofrequency coil array. Here, effects of noise correlations between array elements as well as new correlations introduced by the SMASH reconstruction procedure are assessed. SNR and SNR efficiency in SMASH images are compared with results using traditional array combination strategies. Under optimized conditions, SMASH achieves the same average SNR efficiency as ideal pixel-by-pixel array combinations, while allowing imaging to proceed at otherwise unattainable speeds. The k-space nature of SMASH reconstructions can lead to oscillatory spatial variations in noise standard deviation, which can produce local enhancements of SNR in particular regions.

Speech activity detector for use in noise reduction system, and methods therefor

Abstract: A system and method for removing noise from a signal containing speech (or a related, information carrying signal) and noise. A speech or voice activity detector (VAD) is provided for detecting whether speech signals are present in individual time frames of an input signal. The VAD comprises a speech detector that receives as input the input signal and examines the input signal in order to generate a plurality of statistics that represent characteristics indicative of the presence or absence of speech in a time frame of the input signal, and generates an output based on the plurality of statistics representing a likelihood of speech presence in a current time frame; and a state machine coupled to the speech detector and having a plurality of states. The state machine receives as input the output of the speech detector and transitions between the plurality of states based on a state at a previous time frame and the output of the speech detector for the current time frame. The state machine generates as output a speech activity status signal based on the state of the state machine, which provides a measure of the likelihood of speech being present during the current time frame. The VAD may be used in a noise reduction system.