Showing papers on "Noise (signal processing) published in 2003"

MIMO capacity through correlated channels in the presence of correlated interferers and noise: a (not so) large N analysis

Abstract: The use of multiple-antenna arrays in both transmission and reception promises huge increases in the throughput of wireless communication systems. It is therefore important to analyze the capacities of such systems in realistic situations, which may include spatially correlated channels and correlated noise, as well as correlated interferers with known channel at the receiver. Here, we present an approach that provides analytic expressions for the statistics, i.e., the moments of the distribution, of the mutual information of multiple-antenna systems with arbitrary correlations, interferers, and noise. We assume that the channels of the signal and the interference are Gaussian with arbitrary covariance. Although this method is valid formally for large antenna numbers, it produces extremely accurate results even for arrays with as few as two or three antennas. We also develop a method to analytically optimize over the input signal covariance, which enables us to calculate analytic capacities when the transmitter has knowledge of the statistics of the channel (i.e., the channel covariance). In many cases of interest, this capacity is very close to the full closed-loop capacity, in which the transmitter has instantaneous channel knowledge. We apply this analytic approach to a number of examples and we compare our results with simulations to establish the validity of this approach. This method provides a simple tool to analyze the statistics of throughput for arrays of any size. The emphasis of this paper is on elucidating the novel mathematical methods used.

Wavelet-based denoising of partial discharge signals buried in excessive noise and interference

Abstract: Achieving acceptable levels of sensitivity during online and/or onsite partial discharge (PD) measurements still continues to remain a very challenging task, primarily due to strong coupling of external (random, discrete spectral and stochastic pulsive) interferences. Many analog and digital approaches have been proposed for suppressing these interferences, and amongst these, rejection of the pulsive type of interferences is known to be very difficult, if not impossible. The time and frequency characteristics of the pulsive interference being very similar to that of the PD pulses is the main reason posing difficulty in their separation. In this paper, a novel, semi-automatic, and empirical wavelet-based method (using multi-resolution signal analysis) is proposed to recover PD pulses, buried in excessive noise/interference comprising of random, discrete spectral, pulsive, and any combination of these interferences occurring simultaneously and overlapping-in-time with the PD pulses. A critical assessment of the proposed method is carried out, by processing both simulated and practically acquired PD signals. The results obtained are also compared with those from the best digital filter (infinite impulse response, IIR and finite impulse response, FIR) method proposed in literature. From the results it emerges that, the wavelet approach is superior and further, has the unique capability of successfully rejecting all the three kinds of interferences, even when PD signals and one or all interferences occur simultaneously and overlap-in-time.

A robust open-source algorithm to detect onset and duration of QRS complexes

Abstract: This paper presents a novel algorithm to detect onset and duration of QRS complexes. After low-pass filtering, the ECG signal is converted to a curve length signal by a transform in which a nonlinear scaling factor is introduced to enhance the QRS complex and to suppress unwanted noise. Adaptive thresholds are applied to the length signal to determine the onset and duration of the QRS complex. The algorithm was evaluated with the complete set of single channel ECGs (signal O) from the MIT-BlH Arrhythmia Database, and achieved a gross QRS sensitivity of 99.65% and a gross QRS positive predictive accuracy of 99.77%. The QRS onset determination is very stable and is insensitive to QRS morphology change. The noise tolerance of the algorithm was evaluated using the MIT-BIH Noise Stress Test Database. The C source code for the single-channel algorithm has been contributed to PhysioToolkit and is freely available from PhysioNet (www.physionet.org).

Small array microphone for acoustic echo cancellation and noise suppression

Abstract: Techniques for canceling echo and suppressing noise using an array microphone and signal processing. In one system, at least two microphones form an array microphone and provide at least two microphone input signals. Each input signal may be processed by an echo canceller unit to provide a corresponding intermediate signal having some echo removed. An echo cancellation control unit receives the intermediate signals and derives a first gain used for echo cancellation. A noise suppression control unit provides at least one control signal used for noise suppression based on background noise detected in the intermediate signals. An echo cancellation and noise suppression unit derives a second gain based on the control signal(s), cancels echo in a designated intermediate signal based on the first gain, and suppresses noise in this intermediate signal based on the second gain. The signal processing may be performed in the frequency domain.

Microarray image enhancement by denoising using stationary wavelet transform

Abstract: Microarray imaging is considered an important tool for large scale analysis of gene expression. The accuracy of the gene expression depends on the experiment itself and further image processing. It's well known that the noises introduced during the experiment will greatly affect the accuracy of the gene expression. How to eliminate the effect of the noise constitutes a challenging problem in microarray analysis. Traditionally, statistical methods are used to estimate the noises while the microarray images are being processed. In this paper, we present a new approach to deal with the noise inherent in the microarray image processing procedure. That is, to denoise the image noises before further image processing using stationary wavelet transform (SWT). The time invariant characteristic of SWT is particularly useful in image denoising. The testing result on sample microarray images has shown an enhanced image quality. The results also show that it has a superior performance than conventional discrete wavelet transform and widely used adaptive Wiener filter in this procedure.

Reducing the effects of noise in non-volatile memories through multiple reads

Abstract: Storage elements are read multiple times and the results are accumulated and averaged for each storage element to reduce the effects of noise or other transients in the storage elements and associated circuits that may adversely affect the quality of the read. Several techniques may be employed, including: A full read and transfer of the data from the storage device to the controller device for each iteration, with averaging performed by the controller; a full read of the data for each iteration, with the averaging performed by the storage device, and no transfer to the controller until the final results are obtained; one full read followed by a number of faster re-reads exploiting the already established state information to avoid a full read, followed by an intelligent algorithm to guide the state at which the storage element is sensed. These techniques may be used as the normal mode of operation, or invoked upon exception condition, depending on the system characteristics. A similar form of signal averaging may be employed during the verify phase of programming. An embodiment of this technique would use a peak-detection scheme. In this scenario, several verify checks are performed at the state prior to deciding if the storage element has reached the target state. If some predetermined portion of the verifies fail, the storage element receives additional programming. These techniques allow the system to store more states per storage element in the presence of various sources of noise.

A wavelet-based method for action potential detection from extracellular neural signal recording with low signal-to-noise ratio

Abstract: We present a method for the detection of action potentials, an essential first step in the analysis of extracellular neural signals. The low signal-to-noise ratio (SNR) and similarity of spectral characteristic between the target signal and background noise are obstacles to solving this problem and, thus, in previous studies on experimental neurophysiology, only action potentials with sufficiently large amplitude have been detected and analyzed. In order to lower the level of SNR required for successful detection, we propose an action potential detector based on a prudent combination of wavelet coefficients of multiple scales and demonstrate its performance for neural signal recording with varying degrees of similarity between signal and noise. The experimental data include recordings from the rat somatosensory cortex, the giant medial nerve of crayfish, and the cutaneous nerve of bullfrog. The proposed method was tested for various SNR values and degrees of spectral similarity. The method was superior to the Teager energy operator and even comparable to or better than the optimal linear detector. A detection ratio higher than 80% at a false alarm ratio lower than 10% was achieved, under an SNR of 2.35 for the rat cortex data where the spectral similarity was very high.

Methods and apparatus for cardiac R-wave sensing in a subcutaneous ECG waveform

Abstract: The present invention uses a R-wave sensing algorithm that uniquely combines an automatic threshold adjustment method with a new noise rejection technique. This algorithm has significant advantages in avoiding the sensing of T-waves, P-waves, and noise/artifacts. Detecting the presence of noise bursts uses features that determine if an R-R interval adjacent to or within the noise signal is valid. Circuitry that discriminates noise signals from R-waves can use any one of several features including, but not limited to, the following: detection events occurring so close together that they are outside normal physiologic heart rates; frequency content that is wider than that of QRS complexes; amplitudes that are different than the adjacent or encompassing R-waves; and amplitudes that display greater than normal variability. The present invention employs multiple discrete thresholds optionally with different decay constants, alone or in combination with one or more substantially constant magnitude sensing threshold.

Low-dose CT of the abdomen: evaluation of image improvement with use of noise reduction filters pilot study.

Abstract: A prospective assessment of improvement in image quality at low–radiation-dose computed tomography (CT) of the abdomen by using noise reduction filters was performed. CT images acquired at standard and 50% reduced tube current were processed with six noise reduction filters and evaluated by three radiologists for image noise, sharpness, contrast, and overall image quality in terms of abdominal organ depiction. Quantitative image noise and contrast-to-noise ratio were measured. Baseline low-dose CT images were significantly worse than standard-dose CT images (P < .05). A statistically significant reduction of noise in low-dose images processed with three filters was noted. In conclusion, use of noise reduction filters decreased image noise at low-dose CT. © RSNA, 2003

A low-power integrated circuit for adaptive detection of action potentials in noisy signals

Abstract: The advent of microelectrode arrays allowing for the simultaneous recording of 100 or more neurons is leading to significant advances in science and medicine. However, the amount of data generated by these arrays presents a technical challenge if these systems are ever to be fully implanted for neuroprosthetic applications. We have developed an algorithm to perform real-time data reduction by detecting action potentials, or "spikes," embedded in a noisy signal. This algorithm is simple enough to be implemented in a mixed-signal integrated circuit consuming less than 60 /spl mu/W of power. Experimental results from a chip show that the circuit is able to adaptively set a spike detection threshold above the background noise level of a signal.

Detection and false-alarm probabilities for laser radars that use Geiger-mode detectors.

Abstract: For a direct-detection laser radar that uses a Geiger-mode detector, theory shows that the single-pulse detection probability is reduced by a factor exp(-K), where K is the mean number of primary electrons created by noise in the interval t between detector turn-on and arrival of laser photons reflected from the target. The corresponding false-alarm probability is at least 1 - exp(-K). For fixed-rate noise, one can improve the detection and false-alarm probabilities by reducing t. Moreover, when background-light noise is significant and dominates dark-current noise and when the laser signal is of the order of ten photoelectrons or more, the probabilities can be improved by reducing the amount of light falling on the detector, even if the laser signal is reduced by the same factor as the background light is. Additional analytical calculations show that identifying coincidences in data from as few as three pulses can reduce the false-alarm probability by orders of magnitude and, for some conditions, can also improve the detection probability.

The resonant retina: exploiting vibration noise to optimally detect edges in an image

Abstract: We show that, far from being a drawback, the ubiquitous presence of random vibrations in vision systems operating from mobile devices can advantageously be used as a fundamental tool for edge detection. Directly inspired by biology, the concept of dynamic retina uses the random spatiotemporal path, traced by a moving receptor that samples the image over time, as the basis for the edge detection operation. We propose a simple mathematical formalization of the dynamic retina concept that shows that the relevant information needed for edge detection is contained in the modulation of the variance of the output signal delivered by the retina. Based on a sequence of observations, we then use a variance estimator to determine the presence of the image edges. Following again a biological inspiration, more specifically focusing on neuron dynamics, we introduce a threshold type estimator and use its local asymptotic normality to optimize, via the Cramer-Rao relation, the value of the threshold. The optimal threshold value coincides with a maximum of the associated Fisher information and the overall process can therefore be directly interpreted as a stochastic resonance. We end our contribution by reporting some simple experimental illustrations.

Method and system for processing subband signals using adaptive filters

Abstract: A method and system for processing subband signals using adaptive filters is provided. The system is implemented on an oversampled WOLA filterbank. Inputs signals are oversampled. The system includes an adaptive filter for each subband, and the functionality of improving the convergence properties of the adaptive filter. For example, the convergence property is improved by whitening the spectra of the oversampled subband signals and/or affine projection algorithm. The system is applicable to echo and/or noise cancellation. Adaptive step size control, adaptation process control using Double-Talk detector may be implemented. The system may further implement a non-adaptive processing for reducing uncorrelated noise and/or cross-talk resistant adaptive noise cancellation.

Advanced PD inference in on-field measurements. II. Identification of defects in solid insulation systems

Abstract: Results of investigations performed to evaluate the effectiveness of a new inference method for the diagnosis of solid insulation systems, based on partial discharge (PD) measurements, are reported in this paper. Signal separation, noise recognition, and PD source identification are the main features of the proposed inference method. Techniques for signal separation and automatic noise rejection are reported in the 1st part of this paper, while the problem of the identification of PD phenomena, occurring in defects of insulation systems, is approached in this 2nd part. The identification is based on fuzzy logic and enables the recognition of PD generated from different basic sources, such as internal, surface and corona discharges. It is shown that the different source typologies can be identified by means of fuzzy rules applied to a selection of parameters derived from PD-pulse phase and amplitude distribution analysis, once PD phenomena have been clustered in homogeneous class through a fuzzy algorithm based on PD-pulse shape. The proposed identification procedure is finally applied to rotating machines and cables, affected by insulation defects, showing promising on-field applications.

Method for statistically reconstructing images from a plurality of transmission measurements having energy diversity and image reconstructor apparatus utilizing the method

Abstract: A method for statistically reconstructing images from a plurality of transmission measurements having energy diversity and image reconstructor apparatus utilizing the method are provided. A statistical (maximum-likelihood) method for dual-energy X-ray CT accommodates a wide variety of potential system configurations and measurement noise models. Regularized methods (such as penalized-likelihood or Bayesian estimations) are straightforward extensions. One version of the algorithm monotonically decreases the negative log-likelihood cost function each iteration. An ordered-subsets variation of the algorithm provides a fast and practical version. The method and apparatus provide material characterization and quantitatively accurate CT values in a variety of applications. The method and apparatus provide improved noise/dose properties.

Digital image steganography using stochastic modulation

Abstract: In this paper, we present a new steganographic paradigm for digital images in raster formats. Message bits are embedded in the cover image by adding a weak noise signal with a specified but arbitrary probabilistic distribution. This embedding mechanism provides the user with the flexibility to mask the embedding distortion as noise generated by a particular image acquisition device. This type of embedding will lead to more secure schemes because now the attacker must distinguish statistical anomalies that might be created by the embedding process from those introduced during the image acquisition itself. Unlike previously proposed schemes, this new approach, that we call stochastic modulation, achieves oblivious data transfer without using noise extraction algorithms or error correction. This leads to higher capacity (up to 0.8 bits per pixel) and a convenient and simple implementation with low embedding and extraction complexity. But most importantly, because the embedding noise can have arbitrary properties that approximate a given device noise, the new method offers better security than existing methods. At the end of this paper, we extend stochastic modulation to a content-dependent device noise and we also discuss possible attacks on this scheme based on the most recent advances in steganalysis.

Method and system for power line network fault detection and quality monitoring

Abstract: Fault detection and power network quality monitoring are performed for a power line network using power line communications (“PLC”) signal transceiving and data processing capabilities. Power line signals are continuously received and processed to obtain signal data representative of power line network operating conditions that are expressed in the received power line signals. The harmonic content and noise signature of the signal data are evaluated with reference to known fault signature data and power line network topology properties for detecting and identifying the location of an existing or anticipated fault in the power line network and assessing power transmission quality of the network.

Signal processing using the Teager Energy Operator and other nonlinear operators

Abstract: The Teager Energy Operator is a nonlinear operator defined for both continuous and discrete time signals. In this thesis we define different versions and extensions of the one-dimensional operator, and then look at the properties and positivity of the operator. Its connection to Volterra systems is explained. The Teager Energy Operator is used for demodulation of AM-FM signals, and we look at how this can be done using the operator and nonlinear methods (Hilbert transform, Prony's, Modified covariance, etc). As the Teager Energy Operator is sensitive to noise, the multiband demodulation technique is introduced to refine the estimates. The performance of linear and nonlinear differentiators is investigated. An application to speech analysis is shown, using a multiband method to locate formants in speech. Finally, a performance comparison in different levels of noise is done.

Can noise reduction filters improve low-radiation-dose chest CT images? Pilot study.

Abstract: Effect of noise reduction filters on chest computed tomographic (CT) images acquired with 50% radiation dose reduction was evaluated. Two sets of images were acquired with multi-detector row CT at standard (220-280 mA) and 50% reduced (110-140 mA) tube current at the level of the carina. After postprocessing with six noise reduction filters, images were compared with baseline standard-dose images for noise, sharpness, and contrast in lungs, mediastinum, and chest wall. Quantitative image noise was measured in descending thoracic aorta. Modulation transfer functions were calculated from CT images of 50-microm wire. Noise reduction filters reduced image noise on low-radiation-dose chest CT images, with some compromise in image sharpness and contrast assessed qualitatively, and slightly altered modulation transfer function at higher spatial frequencies.

Deterministic phase unwrapping in the presence of noise.

Abstract: We present a new Fourier-based exact solution for deterministic phase unwrapping from experimental maps of wrapped phase in the presence of noise and phase vortices. This single-step approach has superior performance for images with high phase gradients or insufficient digital sampling approaching 2π/pixel and therefore performs as a fast and practical solution for the phase-unwrapping problem for experimental applications in applied optics, physics, and medicine.

Binaural adaptive hearing aid

Abstract: A system and method for processing an acoustic input signal and providing at least one output acoustic signal to a user of a hearing-aid system. The hearing-aid system includes first and second channels with one of the channels having an adaptive delay. The first channel includes a directional unit for receiving the acoustic input signal and providing a directional signal; a correlative unit for receiving the directional signal and providing a noise reduced signal by utilizing correlative measures for identifying a speech signal of interest in the directional signal; and, a compensator for receiving the noise reduced signal and providing a compensated signal for compensating for a hearing loss of the user.

Small array microphone for beam-forming and noise suppression

Abstract: Techniques are provided to suppress noise and interference using an array microphone and a combination of time-domain and frequency-domain signal processing. In one design, a noise suppression system includes an array microphone, at least one voice activity detector (VAD), a reference generator, a beam-former, and a multi-channel noise suppressor. The array microphone includes multiple microphones—at least one omni-directional microphone and at least one uni-directional microphone. Each microphone provides a respective received signal. The VAD provides at least one voice detection signal used to control the operation of the reference generator, beam-former, and noise suppressor. The reference generator provides a reference signal based on a first set of received signals and having desired voice signal suppressed. The beam-former provides a beam-formed signal based on a second set of received signals and having noise and interference suppressed. The noise suppressor further suppresses noise and interference in the beam-formed signal.

Noise Radar for range/Doppler processing and digital beamforming using low-bit ADC

Abstract: Pulse compression radar is used in a great number of radar applications. Excellent range resolution and high resistance to electronic countermeasures (ECM) can be achieved by long wideband modulated pulses, which spread out the transmitted energy in frequency and time. By using random noise as the waveform, the range ambiguity can be suppressed as well. In this paper, noise radar for Doppler/range indication and digital beamforming is described. Main factors influencing the resolution and sidelobe level in range and Doppler are surveyed. In particular, the possible use of binary or low-bit analog-to-digital converters (ADCs) in noise radar is analyzed, which highly improves the signal-processing rate and reduces the costs. The very significant improvement of sidelobe suppression, when an extra noise signal is added before ADC, is explained theoretically and confirmed by simulation results. Mostly, the random signal is transmitted directly from a noise generating high-frequency source. A sine wave, which is phase or frequency modulated by random noise, is an alternative, giving lower range sidelobes, and higher transmitted mean power when peak-limited transmitters are applied. The dynamic requirements and the bandwidth of the modulating signal can be reduced as well.

Simple methods for detecting zero crossing

Abstract: Affects of noise, harmonics, and multi-frequency signal make frequency and period measurements difficult for synchronizing control events. Various methods are presented to minimize errors in period and phase measurements. Both frequency and amplitude domain approaches are analyzed. Post detection processing allows greater accuracy. Static and dynamic hystereses as well as interpolation methods of zero-crossing detection are investigated.

Electrode systems and methods for reducing motion artifact

Abstract: An electrode system for reducing noise from an electronic signal, the system including an electrode that provides the electronic signal, and a sensor that senses motion and provides a motion signal. The electrode system includes a controller that determines a noise value based on an analysis of the motion signal, and subtracts the noise value from the electronic signal. The electrode system can reduce or eliminate motion artifact from an electronic signal that can result in misdiagnosis, prolong procedural duration and inappropriate treatment of a patient.

Advanced signal processing for power line communications

Abstract: In this article, signal processing techniques to combat the adverse communications environment on power lines are addressed, so as to enable reliable high speed data communications over low-voltage power distribution networks for Internet access and in-home/office networking. It is seen that multicarrier code-division multiple access, multiuser detection, and turbo decoding, having demonstrated their limit-approaching capacity in DSL and wireless communication systems, are readily applied to power line communications. In particular, it is argued that these methods can successfully mitigate the influence of the principal impairments in PLC channels: time-varying channel attenuation, multipath frequency-selective fading, multiple access interference, and background noise. Strategies to deal with the most unfavorable noise source, the impulse noise, are also discussed.