Spatial prediction filtering in the t-x and f-x domains

Geophysics ◽  
1991 ◽  
Vol 56 (12) ◽  
pp. 2019-2026 ◽  
Author(s):  
Scott Hornbostel
Keyword(s):  
Adaptive Filtering ◽  
Wiener Filter ◽  
Spatial Prediction ◽  
Seismic Signals ◽  
Coherent Noise ◽  
New Approach ◽  
Noise Characteristics ◽  
Signal Changes ◽  
Filter Approach ◽  
Data Signal

The predictability of seismic signals from nearby traces can be a powerful tool for reducing random or locally coherent noise. The choice of algorithm to reduce noise for a given application is a function of the data signal and noise characteristics. When the signal and noise are relatively consistent over a given design window, an f-x domain Wiener‐filter approach can be used. For cases in which the data are time‐ or space‐varying, a new approach using 2-D adaptive filtering in the t-x domain can be very effective. In either of these approaches, a prediction trace‐gap can often be successfully used to remove locally coherent noise when lateral signal changes are not too rapid.

A KALMAN FILTER APPROACH TO THE DECONVOLUTION OF SEISMIC SIGNALS

Geophysics ◽  
1974 ◽  
Vol 39 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Norman D. Crump
Keyword(s):  
Kalman Filter ◽  
Wiener Filter ◽  
Seismic Signal ◽  
Seismic Signals ◽  
Discrete State ◽  
Seismic Wavelet ◽  
State Variable ◽  
Deconvolution Technique ◽  
Reflectivity Function ◽  
Filter Approach

It is common practice to model a reflection seismogram as a convolution of the reflectivity function of the earth and an energy waveform referred to as the seismic wavelet. The objective of the deconvolution technique described here is to extract the reflectivity function from the reflection seismogram. The most common approach to deconvolution has been the design of inverse filters based on Wiener filter theory. Some of the disadvantages of the inverse filter approach may be overcome by using a state variable representation of the earth’s reflectivity function and the seismic signal generating process. The problem is formulated in discrete state variable form to facilitate digital computer processing of digitized seismic signals. The discrete form of the Kalman filter is then used to generate an estimate of the reflectivity function. The principal advantages of this technique are its capability for handling continually time‐varying models, its adaptability to a large class of models, its suitability for either single or multi‐channel processing, and its potentially high‐resolution capabilities. Examples based on both synthetic and field seismic data illustrate the feasibility of the method.

PARALLEL, LOCALLY CONNECTED ALGORITHMS FOR NONLINEAR ADAPTIVE FILTERING

1993 ◽  
Vol 04 (01) ◽  
pp. 85-98 ◽  
Author(s):  
HASSAN M. AHMED ◽  
FAWAD RAUF
Keyword(s):  
Adaptive Filtering ◽  
Layered Structure ◽  
Adaptive Filters ◽  
Computationally Efficient ◽  
Local Connectivity ◽  
Linear Filters ◽  
New Approach ◽  
Vlsi Layout ◽  
State Dependent ◽  
Nonlinear Adaptive Filtering

A new adaptive modular realization for nonlinear filters is presented whereby construction is both computationally efficient and readily implemented. The proposed layered structure consists of locally connected, locally adapted linear filters. Modularity and local connectivity make efficient VLSI layout easy and amenable to automation. The layered structure is based on "state dependent embedding", a new approach to the design of series based nonlinear adaptive filters.

scholarly journals Active proportional electromyogram controlled functional electrical stimulation system

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Bethel A. C. Osuagwu ◽  
Emily Whicher ◽  
Rebecca Shirley
Keyword(s):  
Electrical Stimulation ◽  
Adaptive Filtering ◽  
Functional Electrical Stimulation ◽  
Comb Filter ◽  
Online Application ◽  
Present Technique ◽  
Filtering Technique ◽  
Stimulation System ◽  
Filter Approach ◽  
Intentional Movement

AbstractNeurophysiological theories and past studies suggest that intention driven functional electrical stimulation (FES) could be effective in motor neurorehabilitation. Proportional control of FES using voluntary EMG may be used for this purpose. Electrical artefact contamination of voluntary electromyogram (EMG) during FES application makes the technique difficult to implement. Previous attempts to date either poorly extract the voluntary EMG from the artefacts, require a special hardware or are unsuitable for online application. Here we show an implementation of an entirely software-based solution that resolves the current problems in real-time using an adaptive filtering technique with an optional comb filter to extract voluntary EMG from muscles under FES. We demonstrated that unlike the classic comb filter approach, the signal extracted with the present technique was coherent with its noise-free version. Active FES, the resulting EMG-FES system was validated in a typical use case among fifteen patients with tetraplegia. Results showed that FES intensity modulated by the Active FES system was proportional to intentional movement. The Active FES system may inspire further research in neurorehabilitation and assistive technology.

HYDROPHONE STREAMER NOISE

Geophysics ◽  
1974 ◽  
Vol 39 (6) ◽  
pp. 781-793 ◽  
Author(s):  
M. Schoenberger ◽  
J. F. Mifsud
Keyword(s):  
Noise Reduction ◽  
Near Field ◽  
Random Noise ◽  
Original System ◽  
Coherent Noise ◽  
Signal Ratio ◽  
Motion Sensitivity ◽  
Noise Characteristics ◽  
Noise Ratio ◽  
Boat Speed

Experiments were performed to determine the noise characteristics of a hydrophone streamer that had incorporated a number of noise reduction features. In the original system, the channels to which the depth‐controller birds were attached were 3 to 4 times noisier than nonbird channels. Fortunately, the bird noise is near‐field and is eliminated simply by increasing bird/hydrophone separation to 9 ft. On this cable, no other discrete noise sources are evident. The boat, propulsion system, lead‐in cable, tail buoy, and ambient sea conditions (moderate seas) do not generate significant noise at towing speeds above 5 knots. The noise on individual hydrophones not near birds is mainly random with only a small coherent component traveling horizontally through the water from the direction of the boat. However, since the 145-ft hydrophone arrays of 20 detectors are much more effective in reducing random noise than coherent noise, the array output consists of approximately equal portions of each. A twofold decrease in the total noise‐to‐signal ratio would result from doubling the array length (to 290 ft) while maintaining the same hydrophone density. This would result in a four to fivefold decrease in the coherent noise‐to‐signal ratio and a 30 percent decrease in the random noise‐to‐signal ratio. Additional noise reduction would result from increasing the hydrophone density and decreasing the motion sensitivity of the hydrophones. (The streamer hydrophones are not the motion canceling type.) At a towing speed of 5.3 knots, the noise level recorded on an array (not near a bird) is equivalent to pressures of 1 μbar. In normal operations with an 8-gun sleeve exploder source, a stacked section signal‐to‐towing noise ratio of 3 was obtained at 3.0 sec. However, the towing noise increases as the cube of the boat speed, and the S/N ratio would decrease by a factor of 11 if the boat speed were doubled. Conversely, decreasing the boat speed by 18 percent would double the signal‐to‐towing noise ratio.

A Wiener filter approach to shape from shading

2017 ◽  
Author(s):  
Oscar E. Castillo ◽  
Jorge Luis Flores Nuñez ◽  
Jose A. Muñoz ◽  
Ricardo Legarda
Keyword(s):  
Wiener Filter ◽  
Shape From Shading ◽  
Filter Approach

Physical Wavelet Frame Denoising

Geophysics ◽  
2003 ◽  
Vol 68 (1) ◽  
pp. 225-231 ◽  
Author(s):  
Rongfeng Zhang ◽  
Tadeusz J. Ulrych
Keyword(s):  
Seismic Data ◽  
Noise Suppression ◽  
Real Data ◽  
Wavelet Denoising ◽  
Seismic Signals ◽  
Wavelet Frame ◽  
New Approach ◽  
Design And Implementation ◽  
Ground Roll ◽  
Acoustic Processing

This paper deals with the design and implementation of a new wavelet frame for noise suppression based on the character of seismic data. In general, wavelet denoising methods widely used in image and acoustic processing use well‐known conventional wavelets which, although versatile, are often not optimal for seismic data. The new approach, physical wavelet frame denoising uses a wavelet frame that takes into account the characteristics of seismic data both in time and space. Synthetic and real data tests show that the approach is effective even for seismic signals contaminated by strong noise which may be random or coherent, such as ground roll or air waves.

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