An approach for images with low-frequency noise denoising via pre-emphasis and high-pass filter

2013 ◽  
Author(s):  
Qi Zhang ◽  
Shaobo Ma ◽  
Li Cao
Keyword(s):  
Low Frequency ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Pass Filter ◽  
High Pass Filter ◽  
High Pass

Construction of a High-Pass Digital Filter from a Low-Pass Digital Filter

1994 ◽  
Vol 10 (4) ◽  
pp. 374-381 ◽  
Author(s):  
Stephen D. Murphy ◽  
D. Gordon E. Robertson
Keyword(s):  
Digital Filter ◽  
Low Frequency ◽  
Frequency Noise ◽  
Band Pass Filter ◽  
Low Frequency Noise ◽  
Pass Filter ◽  
Low Pass Filter ◽  
High Pass Filter ◽  
Low Pass ◽  
High Pass

To remove low-frequency noise from data such as DC-bias from electromyo-grams (EMGs) or drift from force transducers, a high-pass filter was constructed from a low-pass filter of known characteristics. A summary of the necessary steps required to transform the low-pass digital were developed. Contaminated EMG and force platform data were used to test the filter. The high-pass filter successfully removed the low-frequency noise from the EMG signals. The high-pass filter was then cascaded with the low-pass filter to produce a band-pass filter to enable simultaneous high- and low-frequency noise reduction.

Pulse-shape distortion introduced by broadband deconvolution

1992 ◽  
Vol 82 (1) ◽  
pp. 238-258
Author(s):  
Stuart A. Sipkin ◽  
Arthur L. Lerner-Lam
Keyword(s):  
Transfer Function ◽  
Ground Motion ◽  
Low Frequency ◽  
Frequency Noise ◽  
Low Frequencies ◽  
Pass Filter ◽  
Long Period ◽  
High Pass Filter ◽  
Low Pass ◽  
High Pass

Abstract The availability of broadband digitally recorded seismic data has led to an increasing number of studies using data from which the instrument transfer function has been deconvolved. In most studies, it is assumed that raw ground motion is the quantity that remains after deconvolution. After deconvolving the instrument transfer function, however, seismograms are usually high-pass filtered to remove low-frequency noise caused by very long-period signals outside the frequency band of interest or instabilities in the instrument response at low frequencies. In some cases, data must also be low-pass filtered to remove high-frequency noise from various sources. Both of these operations are usually performed using either zero-phase (acausal) or minimum-phase (causal) filters. Use of these filters can lead to either bias or increased uncertainty in the results, especially when taking integral measures of the displacement pulse. We present a deconvolution method, based on Backus-Gilbert inverse theory, that regularizes the time-domain deconvolution problem and thus mitigates any low-frequency instabilities. We apply a roughening constraint that minimizes the long-period components of the deconvolved signal along with the misfit to the data, emphasizing the higher frequencies at the expense of low frequencies. Thus, the operator acts like a high-pass filter but is controlled by a trade-off parameter that depends on the ratio of the model variance to the residual variance, rather than an ad hoc selection of a filter corner frequency. The resulting deconvolved signal retains a higher fidelity to the original ground motion than that obtained using a postprocess high-pass filter and eliminates much of the bias introduced by such a filter. A smoothing operator can also be introduced that effectively applies a low-pass filter. This smoothing is useful in the presence of blue noise, or if inferences about source complexity are to be made from the roughness of the deconvolved signal.

Original waveform of lung sound crackles: a case study of the effect of high-pass filtration

1991 ◽  
Vol 71 (6) ◽  
pp. 2173-2177 ◽  
Author(s):  
T. Katila ◽  
P. Piirila ◽  
K. Kallio ◽  
E. Paajanen ◽  
T. Rosqvist ◽  
...  
Keyword(s):  
Low Frequency ◽  
Final Analysis ◽  
Sound Signal ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Lung Sound ◽  
High Pass

In lung sound research, low-frequency noise usually disturbs the sound signal being recorded. Some researchers therefore use high-pass filtration before the final analysis. In this study, the effect of digital and analog high-pass filtration on the morphology of the lung sound crackles is evaluated. The original nonprefiltered crackle waveform is presented, and the effect of the high-pass filtration on the crackle waveform characteristics is elucidated in one patient with silicoasbestosis.

scholarly journals Relationship between blood pressure and cerebral blood flow during supine cycling: influence of aging

2016 ◽  
Vol 120 (5) ◽  
pp. 552-563 ◽  
Author(s):  
Jonathan D. Smirl ◽  
Keegan Hoffman ◽  
Yu-Chieh Tzeng ◽  
Alex Hansen ◽  
Philip N. Ainslie
Keyword(s):  
Blood Pressure ◽  
Lower Body Negative Pressure ◽  
Function Analysis ◽  
Low Frequency ◽  
Moderate Intensity ◽  
Pass Filter ◽  
High Pass Filter ◽  
Age Related ◽  
Transfer Function Analysis ◽  
High Pass

The cerebral pressure-flow relationship can be quantified as a high-pass filter, where slow oscillations are buffered (<0.20 Hz) and faster oscillations are passed through relatively unimpeded. During moderate intensity exercise, previous studies have reported paradoxical transfer function analysis (TFA) findings (altered phase or intact gain). This study aimed to determine whether these previous findings accurately represent this relationship. Both younger (20–30 yr; n = 10) and older (62–72 yr; n = 9) adults were examined. To enhance the signal-to-noise ratio, large oscillations in blood pressure (via oscillatory lower body negative pressure; OLBNP) were induced during steady-state moderate intensity supine exercise (∼45–50% of heart rate reserve). Beat-to-beat blood pressure, cerebral blood velocity, and end-tidal Pco2 were monitored. Very low frequency (0.02–0.07 Hz) and low frequency (0.07–0.20 Hz) range spontaneous data were quantified. Driven OLBNP point estimates were sampled at 0.05 and 0.10 Hz. The OLBNP maneuvers augmented coherence to >0.97 at 0.05 Hz and >0.98 at 0.10 Hz in both age groups. The OLBNP protocol conclusively revealed the cerebrovascular system functions as a high-pass filter during exercise throughout aging. It was also discovered that the older adults had elevations (+71%) in normalized gain (+0.46 ± 0.36%/%: 0.05 Hz) and reductions (−34%) in phase (−0.24 ± 0.22 radian: 0.10 Hz). There were also age-related phase differences between resting and exercise conditions. It is speculated that these age-related changes in the TFA metrics are mediated by alterations in vasoactive factors, sympathetic tone, or the mechanical buffering of the compliance vessels.

Notizen: A Contribution to the Stark-Spectroscopy at Low Microwave Frequencies

1979 ◽  
Vol 34 (7) ◽  
pp. 903-905 ◽  
Author(s):  
W. Schrepp ◽  
H. Dreizler
Keyword(s):  
Double Resonance ◽  
Low Frequency ◽  
Frequency Region ◽  
Absorption Cell ◽  
Stark Spectroscopy ◽  
Pass Filter ◽  
Square Wave ◽  
High Pass Filter ◽  
High Pass ◽  
Lower Frequencies

Recently we published a construction of a micro­wave-microwave double resonance spectrometer [1], which allows a variety of experiments. An essential part of it is a “stripline” absorption cell.Although Stark-Spectroscopy [2] gave a very important impetus to the investigation of rotation spectra and is in use for three decades, measure­ments below 6.5 GHz are few in number compared to the frequency region above 6.5 GHz.The reason is that generally the line intensity decreases at lower frequencies and the cross sections of the standard waveguides are larger. If one does not use special waveguides * a higher Stark voltage has to be applied to produce the necessary Stark field for modulation. This requires a rather powerful Stark square wave generator** to load and unload the capacity of the absorption cell.Measurements in the low frequency region may be useful since at these lower frequencies the density of rotational spectra is sometimes considerably lower than at higher frequencies, which faciliates the assignement.We noticed that the stripline cell, which transmits from DC to 18 GHz in a coaxial type mode, may be used for Stark-Spektroscopy by feeding the Stark voltage and the microwave simultaneously to the septum. After having finished our experiments, we noticed that S. Weisbaum [4] et al. measured the transitions 32 - 3a and 52 - 53 of HDO at 486.50 and 824.64 MHz, respectively, by a similar tech­nique. The radiofrequency was connected together with the Stark voltage to the septum of a conven­tional Stark cell.In Fig. 1 we give the details of the set up. To combine the microwave and the square wave we use “monitor tees” *. The square wave is fed into the monitor port which transmits a 100 kHz square wave. For example, a residual square wave of 140 V is observed at the microwave port when applying a 400 V square wave. To prevent any influence of the square wave on the microwave sourcje we use a piece of waveguide as a high pass filter. At the output of the absorption cell another piece af waveguide acting as a high pass filter protects the detector cristal. The cell we used for the measurements presented in Table 1 and Fig. 2 is made of an X-band waveguide R100 (cut off for the TE10-mode 6.56GHz). The construction is similar to that given in Fig. 1 of the previous paper [1], but TNC connectors** are used. The cell has been tested for a voltage of 2500 V between septum and the waveguide walls. The attenuation of the microwave on the stripline between 0.4 and 2.4 GHz is about 1.5 dB.

Low-frequency noise attenuation in seismic and microseismic data using mathematical morphological filtering

2020 ◽  
Vol 222 (3) ◽  
pp. 1728-1749 ◽  
Author(s):  
Weilin Huang ◽  
Runqiu Wang ◽  
Shaohuan Zu ◽  
Yangkang Chen
Keyword(s):  
Frequency Band ◽  
Low Frequency ◽  
Frequency Noise ◽  
Noise Attenuation ◽  
Low Frequency Noise ◽  
Frequency Signal ◽  
Filtering Method ◽  
Morphological Filtering ◽  
High Pass ◽  
Filtering Approach

SUMMARY Low-frequency noise is one of the most common types of noise in seismic and microseismic data. Conventional approaches, such as the high-pass filtering method, utilize the low-frequency nature and distinguish between signal and noise based on their different frequency contents. However, conventional approaches are limited or even invalid when the signal and noise shares the same frequency band. Moreover, high-pass filtering method will suppress not only low-frequency noise but also low-frequency signal when they overlap in a same frequency band, which is extremely important in the inversion process for building the subsurface velocity model. To overcome the drawbacks of conventional high-pass filtering approach, we developed a novel method based on the mathematical morphology theorem to separate signal and noise using their differences in morphological scale. We extracted empirical relation between morphological scale and frequency band so that the mathematical morphology based approach can be conveniently used in low-frequency noise attenuation. The proposed method is termed as the mathematical morphological filtering (MMF) method. We compare the MMF approach with high-pass filtering and empirical mode decomposition (EMD) approaches using synthetic, reflection seismic and microseismic examples. The various examples demonstrate that the proposed MMF method can preserve more low-frequency signal than the high-pass filtering approach, and is more efficient and causes fewer artefacts than the EMD approach.

scholarly journals A Chopper-Embedded BGR Composite Noise Reduction Circuit for Clock Generator

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2257
Author(s):  
Neeru Agarwal ◽  
Neeraj Agarwal ◽  
Chih-Wen Lu ◽  
Masahito Oh-e
Keyword(s):  
Flicker Noise ◽  
Noise Analysis ◽  
Low Frequency ◽  
Low Noise ◽  
Frequency Noise ◽  
Clock Generator ◽  
Low Frequency Noise ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Offset Voltage

A chopper-embedded bandgap reference (BGR) scheme is presented using 0.18 μm CMOS technology for low-frequency noise suppression in the clock generator application. As biasing circuitry produce significant flicker noise, along with thermal noise from passive components, the proposed low-noise chopper-stabilized BGR circuit was designed and implemented for wide temperature range of −40 to 125 °C, including a startup and self-biasing circuit to reduce critical low-frequency noise from the bias circuitry and op amp input offset voltage. The BGR circuit generated a reference voltage of 1.25 V for a supply voltage range of 2.5–3.3 V. The gain of the implemented BGR operational transconductance amplifier is 84.1 dB. A non-overlapping clock circuit was implemented to reduce the clock skew effect, which is also one of the noise contributors. The noise analysis of a chopped bandgap voltage reference was evaluated through cadence periodic steady-state (PSS) analysis and periodic noise (PNoise) analysis. The low-frequency flicker noise was reduced from 1.5 to 0.4 μV/sqrt(Hz) at 1 KHz, with the proposed chopping scheme in the bandgap. Comparisons of the noise performance of the chopper-embedded BGR, with and without a low-pass filter, were also performed, and the results show a further reduction in the overall noise. A reduction in the flicker noise, from 181.3 to 10.26 mV/sqrt(Hz) at 100 KHz, was observed with the filter. All circuit blocks of the proposed BGR scheme were designed and simulated using the EDA tool HSPICE, and layout generation was carried out by Laker. The BGR architecture layout dimensions are 285.25 μm × 125.38 μm.

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