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Noise Reduction (noise + reduction)

Distribution by Scientific Domains
Earth and Environmental Science40%

Selected Abstracts

Signal de-noising in magnetic resonance spectroscopy using wavelet transforms

CONCEPTS IN MAGNETIC RESONANCE, Issue 6 2002
Hector F. Cancino-De-Greiff
Abstract Computer signal processing is used for quantitative data analysis (QDA) in magnetic resonance spectroscopy (MRS). The main difficulty in QDA is that MRS signals appear to be contaminated with random noise. Noise reduction can be achieved by coherent averaging, but it is not always possible to average many MRS waveforms. Wavelet shrinkage de-noising (WSD) is a technique that can be employed in this case. The potentialities of WSD in MRS, alone and combined with the Cadzow algorithm, are analyzed through computer simulations. The results can facilitate an appropriate application of WSD, as well as a deeper understanding of this technique. © 2002 Wiley Periodicals, Inc. Concepts Magn Reson 14: 388,401, 2002 [source]

Artificial neural network inversion of magnetotelluric data in terms of three-dimensional earth macroparameters

GEOPHYSICAL JOURNAL INTERNATIONAL, Issue 1 2000
Vjacheslav Spichak
The possibility of solving the three-dimensional (3-D) inverse problem of geoelectrics using the artificial neural network (ANN) approach is investigated. The properties of a supervised ANN based on the back-propagation scheme with three layers of neurons are studied, and the ANN architecture is adjusted. A model class consisting of a dipping dyke in the basement of a two-layer earth with the dyke in contact with the overburden is used for numerical experiments. Six macroparameters of the 3-D model, namely the thickness of the top layer, which coincides with the depth of the dyke (D), the conductivity ratio between the first and second layers (C1,/C2,), the conductivity contrast of the dyke (C/C2,), and the width (W ), length (L ) and dip angle of the dyke (A), are used. Various groups of magnetotelluric field components and their transformations are studied in order to estimate the effect of the data type used on the ANN recognition ability. It is found that use of only the xy - and yx -components of impedance phases results in reasonable recognition errors for all unknown parameters (D: 0.02 per cent, C1/C2: 8.4 per cent, C/C2: 26.8 per cent, W : 0.02 per cent, L : 0.02 per cent, A: 0.24 per cent). The influence of the size and shape of the training data pool (including the ,gaps in education' and ,no target' effects) on the recognition properties is studied. Results from numerous ANN tests demonstrate that the ANN possesses good enough interpolation and extrapolation abilities if the training data pool contains a sufficient number of representative data sets. The effect of noise is estimated by means of mixing the synthetic data with 30, 50 and 100 per cent Gaussian noise. The unusual behaviour of the recognition errors for some of the model parameters when the data become more noisy (in particular, the fact that an increase in error is followed by a decrease) indicates that the use of standard techniques of noise reduction may give an opposite result, so the development of a special noise treatment methodology is required. Thus, it is shown that ANN-based recognition can be successfully used for inversion if the data correspond to the model class familiar to the ANN. No initial guess regarding the parameters of the 3-D target or 1-D layering is required. The ability of the ANN to teach itself using real geophysical (not only electromagnetic) data measured at a given location over a sufficiently long period means that there is the potential to use this approach for interpreting monitoring data. [source]

The feasibility of electromagnetic gradiometer measurements

GEOPHYSICAL PROSPECTING, Issue 3 2001
Daniel Sattel
The quantities measured in transient electromagnetic (TEM) surveys are usually either magnetic field components or their time derivatives. Alternatively it might be advantageous to measure the spatial derivatives of these quantities. Such gradiometer measurements are expected to have lower noise levels due to the negative interference of ambient noise recorded by the two receiver coils. Error propagation models are used to compare quantitatively the noise sensitivities of conventional and gradiometer TEM data. To achieve this, eigenvalue decomposition is applied on synthetic data to derive the parameter uncertainties of layered-earth models. The results indicate that near-surface gradient measurements give a superior definition of the shallow conductivity structure, provided noise levels are 20,40 times smaller than those recorded by conventional EM instruments. For a fixed-wing towed-bird gradiometer system to be feasible, a noise reduction factor of at least 50,100 is required. One field test showed that noise reduction factors in excess of 60 are achievable with gradiometer measurements. However, other collected data indicate that the effectiveness of noise reduction can be hampered by the spatial variability of noise such as that encountered in built-up areas. Synthetic data calculated for a vertical plate model confirm the limited depth of detection of vertical gradient data but also indicate some spatial derivatives which offer better lateral resolution than conventional EM data. This high sensitivity to the near-surface conductivity structure suggests the application of EM gradiometers in areas such as environmental and archaeological mapping. [source]

An efficient method for combining adaptive echo and noise canceller in hands-free systems

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 3 2009
Jafar Ramadhan Mohammed
Abstract Acoustic interferences severely degrade the quality and the intelligibility of the desired speech signal, thus posing a severe problem for many speech applications. Several acoustic echo cancellation (AEC) techniques have been proposed with a view to solving this problem. There are, however, few reports of AEC methods working under real noisy conditions. In this paper, we investigate the maximum positive synergies of the combination of acoustic echo canceller with a new adaptive beamformer. The proposed system achieves both the AEC and noise reduction of speech in an actual environment with real noise sources. Since the AEC is located behind the fixed beamformer of the new adaptive beamformer only one AEC is required for an arbitrary number of array elements, and the AEC does not feel any repercussions from the new adaptive beamformer. The proposed system was implemented in a real environment using National Instruments NI-PXI-1042Q controller system and data acquisition card PXI-4472. Experimental results show that the proposed system has successfully improved the performance of hands-free systems. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Visrock: a program for digital topography and X-ray microdiffraction imaging

JOURNAL OF APPLIED CRYSTALLOGRAPHY, Issue 3 2007
Tilo Baumbach
Visrock is a program for interactive analysis of sequences of digital X-ray images. Visrock was developed in the context of the rocking-curve imaging method of full-field X-ray microdiffraction imaging. Its functionality is based on parallel profile analysis of millions of local diffraction profiles. Options for subsequent visualization of the spatial distribution of extracted parameters include automatic contrast enhancement, noise reduction and multi-peak analysis. In addition to microdiffraction imaging, further useful applications of the program lie particularly in computed tomography, sequential radiography and analyser-based imaging. [source]