scholarly journals Effects of fixed cutoff filtering on dark- and light-adapted ERG components and the application of variable cutoff filter

2021 ◽  
Author(s):  
Min Gao ◽  
Mirella Telles Salgueiro Barboni ◽  
Dora Fix Ventura ◽  
Balázs Vince Nagy
Keyword(s):  
Statistical Tests ◽  
Present Report ◽  
Cutoff Frequency ◽  
Low Frequency ◽  
Oscillatory Potentials ◽  
Transition Range ◽  
Cutoff Frequencies ◽  
Frequency Components ◽  
Filter Frequency ◽  
High Pass

Abstract Purpose Human oscillatory potentials (OPs) are derived from dark-adapted (DA) electroretinograms (ERGs) with fixed frequency cutoff filters while light-adapted (LA) OPs are generally not isolated from ERGs. Our purpose was to analyze the effect of cutoff frequencies on DA and LA ERG components using a series of fixed and variable filters. Methods DA and LA ERGs were recorded from 10 healthy eyes of 10 subjects (mean age = 20.5 ± 6.7 years) following ISCEV standards. Each signal was filtered in the Fourier domain to acquire slow (a- and b-waves; below cutoff frequency) and fast (OPs; above cutoff frequency) components. Fixed cutoff frequencies ranged from 60 to 105 Hz and a variable cutoff frequency was calculated. Results were analyzed with statistical tests and specific models. Results DA ERG components were slightly influenced by the filter cutoff frequency. In contrast, fixed and variable filters significantly changed LA components: the lower the cutoff frequency the smaller the b-wave and OP3 and the higher the OP2/OP4 amplitudes. Analyzing the filter frequency limits a transition range between 68.9 Hz and 83.9 Hz was observed where amplitudes vary. Conclusions The present report shows that DA OPs may be isolated from ERGs using filtering procedures with high-pass cutoff frequency at about 75 Hz as recommended by ISCEV. On the other hand, the spectral distribution of low-frequency and high-frequency LA ERG components may overlap. Accordingly, filtering the signal using different cutoff frequencies is not necessarily separating b-wave and OPs.

Interactive Effects of High-Pass Filtering and Masking Noise on Word Recognition

2005 ◽  
Vol 114 (11) ◽  
pp. 867-878 ◽  
Author(s):  
Saravanan Elangovan ◽  
Andrew Stuart
Keyword(s):  
Hearing Loss ◽  
Word Recognition ◽  
Hearing Impairment ◽  
High Frequency ◽  
Cutoff Frequency ◽  
Low Frequency ◽  
Interactive Effects ◽  
Signal To Noise ◽  
Noise Condition ◽  
High Pass

Objectives: This study sought to examine the word recognition performance in noise of individuals with a simulated low-frequency hearing loss. The goal was to understand how low-frequency hearing impairment affects performance on tasks that challenge temporal processing skills. Methods: Twenty-two normal-hearing young adults participated. Monosyllabic words were presented in continuous and interrupted noise at 3 signal-to-noise ratios of −10, 0, and +10 dB. High-pass filtering of the stimuli at 3 different cutoff frequencies (ie, 1,000, 1,250, and 1,500 Hz) simulated the low-frequency hearing impairment. Results: In general, performance decreased with increasing cutoff frequency, was higher for more favorable signal-to-noise ratios, and was superior in the interrupted condition relative to the continuous noise condition. One important revelation was that the magnitude of the performance superiority observed in the interrupted noise condition did not diminish with high-pass filtering; ie, the release from masking in interrupted noise was preserved. Conclusions: The results of the present study complement previous findings in which this paradigm was used with low-pass filtering to simulate a high-frequency hearing loss. That is to say, low-frequency hearing channels are inherently poorer than high-frequency channels in temporal resolution.

DC-level Detection of Burst-Suppression EEG

1994 ◽  
Vol 33 (01) ◽  
pp. 35-38 ◽  
Author(s):  
T. Lipping ◽  
P. Loula ◽  
V. Jäntti ◽  
A Yli-Hankala
Keyword(s):  
Time Constant ◽  
Cutoff Frequency ◽  
Low Frequency ◽  
Burst Suppression ◽  
Eeg Signal ◽  
Visual Examination ◽  
Mixed Frequency ◽  
Frequency Components

Abstract:The EEG signal is usually recorded with low time constant analog prefilters to avoid low frequency artefacts. During this kind of recording the frequency components below the cutoff frequency of the analog prefilter (usually below about 1 to 3 Hz) are lost. By visual examination of some experimental recordings taken with a higher time constant, it was noticed that during burst-suppression EEG the DC-level of the signal rises sharply when the burst begins and falls when the burst ends. Thus, a burst actually consists of a mixed frequency discharge on a pulse-like DC-shift. We developed a filter algorithm to estimate the change in the DC-level during bursts as accurately as possible.

On a Design of Narrowband FIR Low-Pass Filters

2011 ◽  
pp. 2882-2887
Author(s):  
Gordana Jovanovic Dolecek ◽  
Javier Diaz Carmona
Keyword(s):  
Impulse Response ◽  
High Frequency ◽  
Digital Filters ◽  
Stop Band ◽  
Low Frequency ◽  
Pass Band ◽  
Low Pass ◽  
Frequency Components ◽  
Band Pass ◽  
High Pass

Stearns and David (1996) states that “for many diverse applications, information is now most conveniently recorded, transmitted, and stored in digital form, and as a result, digital signal processing (DSP) has become an exceptionally important modern tool.” Typical operation in DSP is digital filtering. Frequency selective digital filter is used to pass desired frequency components in a signal without distortion and to attenuate other frequency components (Smith, 2002; White, 2000). The pass-band is defined as the frequency range allowed to pass through the filter. The frequency band that lies within the filter stop-band is blocked by the filter and therefore eliminated from the output signal. The range of frequencies between the pass-band and the stop-band is called the transition band and for this region no filter specification is given. Digital filters can be characterized either in terms of the frequency response or the impulse response (Diniz, da Silva & Netto, 2002). Depending on its frequency characteristic, a digital filter is either low-pass, high-pass, band-pass, or band-stop filters. A low-pass (LP) filter passes low frequency components to the output, while eliminating high-frequency components. Conversely, the high-pass (HP) filter passes all high-frequency components and rejects all low-frequency components. The band-pass (BP) filter blocks both low- and high-frequency components while passing the intermediate range. The band-stop (BS) filter eliminates the intermediate band of frequencies while passing both low- and high-frequency components. In terms of their impulse responses digital filters are either infinite impulse response (IIR) or finite impulse response (FIR) digital filters. Each of four types of filters (LP, HP, BP, and BS) can be designed as an FIR or an IIR filter (Ifeachor & Jervis, 2001; Mitra, 2005; Oppenheim & Schafer, 1999).

A Fog-Removing Treatment Based on Combining High-Frequency Emphasis Filtering and Histogram Equalization

2011 ◽  
Vol 474-476 ◽  
pp. 2198-2202
Author(s):  
Xing Zou ◽  
Yu Liu ◽  
Ze Fu Tan ◽  
Cheng Sheng Tu ◽  
Hong Zhang
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Histogram Equalization ◽  
Gray Level ◽  
Exponential Relationship ◽  
Visual Effect ◽  
Cutoff Frequencies ◽  
Highpass Filter ◽  
Frequency Components ◽  
Retinex Theory

Fog may cause the impairment of image as well as the decrease in the distinguish ability. The present paper is to get rid of the weather’s influence from the impaired image. According to Retinex theory and exponential relationship between the degradation of the image and the depths of the scene points, it puts forward a fog-removing treatment based on combining high-frequency emphasis filtering and histogram equalization .Firstly, obtain the padding parameters and fill it. Secondly, filter the impaired image using Butterworth highpass filter of order 2. Through the padding parameters, Highpass filtering is not overly sensitive to the value of cutoff frequencies, as long as the radius of the filter is not so small that frequencies near the origin of the transform are passed. In which the gray-level tonality due to the low-frequency components was retained. Lastly, histogram balanced the image gotten last step. The simulation result based on Matlab shows his algorithm can effectively improve the visual effect scene under the condition of mist.

Simulations of high-resolution images of amorphous silicon films

1986 ◽  
Vol 44 ◽  
pp. 544-545
Author(s):  
G. Y. Fan ◽  
J. M. Cowley
Keyword(s):  
Electron Microscope ◽  
High Frequency ◽  
Fourier Transformation ◽  
Amorphous Materials ◽  
Low Frequency ◽  
Chromatic Aberration ◽  
Structure Information ◽  
Frequency Components ◽  
High Resolution Images ◽  
Spatial Frequency Spectrum

It is well known that the structure information on the specimen is not always faithfully transferred through the electron microscope. Firstly, the spatial frequency spectrum is modulated by the transfer function (TF) at the focal plane. Secondly, the spectrum suffers high frequency cut-off by the aperture (or effectively damping terms such as chromatic aberration). While these do not have essential effect on imaging crystal periodicity as long as the low order Bragg spots are inside the aperture, although the contrast may be reversed, they may change the appearance of images of amorphous materials completely. Because the spectrum of amorphous materials is continuous, modulation of it emphasizes some components while weakening others. Especially the cut-off of high frequency components, which contribute to amorphous image just as strongly as low frequency components can have a fundamental effect. This can be illustrated through computer simulation. Imaging of a whitenoise object with an electron microscope without TF limitation gives Fig. 1a, which is obtained by Fourier transformation of a constant amplitude combined with random phases generated by computer.

Trombone Transfer Functions: Comparison Between Frequency-Swept Sine Wave and Human Performer Input

2012 ◽  
Vol 37 (4) ◽  
pp. 447-454
Author(s):  
James W. Beauchamp
Keyword(s):  
Transfer Function ◽  
Transfer Functions ◽  
Cutoff Frequency ◽  
Sine Wave ◽  
Nonlinear Propagation ◽  
Linear Filter ◽  
Wave System ◽  
General Effect ◽  
Filter Characteristic ◽  
High Pass

Abstract Source/filter models have frequently been used to model sound production of the vocal apparatus and musical instruments. Beginning in 1968, in an effort to measure the transfer function (i.e., transmission response or filter characteristic) of a trombone while being played by expert musicians, sound pressure signals from the mouthpiece and the trombone bell output were recorded in an anechoic room and then subjected to harmonic spectrum analysis. Output/input ratios of the signals’ harmonic amplitudes plotted vs. harmonic frequency then became points on the trombone’s transfer function. The first such recordings were made on analog 1/4 inch stereo magnetic tape. In 2000 digital recordings of trombone mouthpiece and anechoic output signals were made that provide a more accurate measurement of the trombone filter characteristic. Results show that the filter is a high-pass type with a cutoff frequency around 1000 Hz. Whereas the characteristic below cutoff is quite stable, above cutoff it is extremely variable, depending on level. In addition, measurements made using a swept-sine-wave system in 1972 verified the high-pass behavior, but they also showed a series of resonances whose minima correspond to the harmonic frequencies which occur under performance conditions. For frequencies below cutoff the two types of measurements corresponded well, but above cutoff there was a considerable difference. The general effect is that output harmonics above cutoff are greater than would be expected from linear filter theory, and this effect becomes stronger as input pressure increases. In the 1990s and early 2000s this nonlinear effect was verified by theory and measurements which showed that nonlinear propagation takes place in the trombone, causing a wave steepening effect at high amplitudes, thus increasing the relative strengths of the upper harmonics.

ANALYSIS OF STAND RESEARCH RESULTS OF AXIAL DYNAMIC FORCE IN DRILLING BY THREE ROLLER CONE BIT

2019 ◽  
pp. 81-93
Author(s):  
В. М. Мойсишин ◽  
M. V. Lyskanych ◽  
R. A. Zhovniruk ◽  
Ye. P. Majkovych
Keyword(s):  
Low Frequency ◽  
Maximum Energy ◽  
Dynamic Force ◽  
Low Frequency Oscillation ◽  
Drilling Tool ◽  
Rock Destruction ◽  
Frequency Components ◽  
Harmonic Components ◽  
Experimental Values ◽  
Harmful Effects

The purpose of the proposed article is to establish the causes of oscillations of drilling tool and the basic laws of the distribution of the total energy of the process of changing the axial dynamic force over frequencies of spectrum. Variable factors during experiments on the classical plan were the rigidity of drilling tool and the hardness of the rock. According to the results of research, the main power of the process of change of axial dynamic force during drilling of three roller cone bits is in the frequency range 0-32 Hz in which three harmonic frequency components are allocated which correspond to the theoretical values of low-frequency and gear oscillations of the chisel and proper oscillations of the bit. The experimental values of frequencies of harmonic components of energy and normalized spectrum as well as the magnitude of the dispersion of the axial dynamic force and its normalized values at these frequencies are presented. It has been found that with decreasing rigidity of the drilling tool maximum energy of axial dynamic force moves from the low-frequency oscillation region to the tooth oscillation area, intensifying the process of rock destruction and, at the same time, protecting the tool from the harmful effects of the vibrations of the bit. Reducing the rigidity of the drilling tool protects the bit from the harmful effects of the vibrations generated by the stand. The energy reductions in these fluctuations range from 47 to 77%.

A Novel Adaptive PET/CT Image Fusion Algorithm

2019 ◽  
Vol 14 (7) ◽  
pp. 658-666
Author(s):  
Kai-jian Xia ◽  
Jian-qiang Wang ◽  
Jian Cai
Keyword(s):  
Lung Cancer ◽  
Image Fusion ◽  
High Frequency ◽  
Malignant Tumors ◽  
Low Frequency ◽  
Combination Method ◽  
Ct Image ◽  
Fusion Algorithm ◽  
Pet Ct ◽  
Frequency Components

Background: Lung cancer is one of the common malignant tumors. The successful diagnosis of lung cancer depends on the accuracy of the image obtained from medical imaging modalities. Objective: The fusion of CT and PET is combining the complimentary and redundant information both images and can increase the ease of perception. Since the existing fusion method sare not perfect enough, and the fusion effect remains to be improved, the paper proposes a novel method called adaptive PET/CT fusion for lung cancer in Piella framework. Methods: This algorithm firstly adopted the DTCWT to decompose the PET and CT images into different components, respectively. In accordance with the characteristics of low-frequency and high-frequency components and the features of PET and CT image, 5 membership functions are used as a combination method so as to determine the fusion weight for low-frequency components. In order to fuse different high-frequency components, we select the energy difference of decomposition coefficients as the match measure, and the local energy as the activity measure; in addition, the decision factor is also determined for the high-frequency components. Results: The proposed method is compared with some of the pixel-level spatial domain image fusion algorithms. The experimental results show that our proposed algorithm is feasible and effective. Conclusion: Our proposed algorithm can better retain and protrude the lesions edge information and the texture information of lesions in the image fusion.

Underwater Image Enhancement Method Combining color and Luminance

2020 ◽  
Vol 13 ◽  
Author(s):  
ZHAO Baiting ◽  
WANG Feng ◽  
JIA Xiaofen ◽  
GUO Yongcun ◽  
WANG Chengjun
Keyword(s):  
Image Enhancement ◽  
Color Space ◽  
Low Frequency ◽  
Brightness Enhancement ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method ◽  
Frequency Components ◽  
Image Contour ◽  
Objective Indicators

Background:: Aiming at the problems of color distortion, low clarity and poor visibility of underwater image caused by complex underwater environment, a wavelet fusion method UIPWF for underwater image enhancement is proposed. Methods:: First of all, an improved NCB color balance method is designed to identify and cut the abnormal pixels, and balance the color of R, G and B channels by affine transformation. Then, the color correction map is converted to CIELab color space, and the L component is equalized with contrast limited adaptive histogram to obtain the brightness enhancement map. Finally, different fusion rules are designed for low-frequency and high-frequency components, the pixel level wavelet fusion of color balance image and brightness enhancement image is realized to improve the edge detail contrast on the basis of protecting the underwater image contour. Results:: The experiments demonstrate that compared with the existing underwater image processing methods, UIPWF is highly effective in the underwater image enhancement task, improves the objective indicators greatly, and produces visually pleasing enhancement images with clear edges and reasonable color information. Conclusion:: The UIPWF method can effectively mitigate the color distortion, improve the clarity and contrast, which is applicable for underwater image enhancement in different environments.

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