Relevant bibliographies by topics / Cross Correlation Peak

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Cross Correlation Peak'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Cross Correlation Peak"

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Chen, Chulung, and Jian-Shuen Fang. "Cross-correlation peak optimization on joint transform correlators." Optics Communications 178, no. 4-6 (May 2000): 315–22. http://dx.doi.org/10.1016/s0030-4018(00)00683-0.

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Mueller, Leonard J., Douglas W. Elliott, Garett M. Leskowitz, Jochem Struppe, Ryan A. Olsen, Kee-Chan Kim, and Christopher A. Reed. "Uniform-sign cross-peak double-quantum-filtered correlation spectroscopy." Journal of Magnetic Resonance 168, no. 2 (June 2004): 327–35. http://dx.doi.org/10.1016/j.jmr.2004.03.017.

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Jiang, Nan, and Jian Wang. "The Theoretical Limits of Watermark Spread Spectrum Sequence." Scientific World Journal 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/432740.

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At present, the spread spectrum (SS) sequences used in watermark include i.i.d. random sequences and the sequences used in SS communications. They appear earlier than digital watermark. Almost no researchers pay attention to whether they are really fit for watermark. In this paper, we compare the SS watermark channel and the traditional SS communication channel. We find out that their correlation property is different. Considering cropping and translation attacks, we define watermark auto- and cross-correlation and propose Loose Autocorrelation and Tight Cross-Correlation (LAC&TCC) properties for SS watermark. The LAC&TCC properties are that, whether or not synchronized, the autocorrelation is equal or close to 1 and the cross-correlation is equal or close to 0. Accordingly, the peak correlation is divided into the peak autocorrelationRa(l)and the peak cross-correlationRc(l). We establish the lower bound ofRc(l)and the higher bound ofRa(l), respectively. The two bounds indicate that, no matter how small the cover is reserved, the extractor can always find a threshold to distinguish auto- and cross-correlation in theory.
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Shim, J., S. Codis, C. Pichon, D. Pogosyan, and C. Cadiou. "The clustering of critical points in the evolving cosmic web." Monthly Notices of the Royal Astronomical Society 502, no. 3 (February 9, 2021): 3885–910. http://dx.doi.org/10.1093/mnras/stab263.

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ABSTRACT Focusing on both small separations and baryonic acoustic oscillation scales, the cosmic evolution of the clustering properties of peak, void, wall, and filament-type critical points is measured using two-point correlation functions in ΛCDM dark matter simulations as a function of their relative rarity. A qualitative comparison to the corresponding theory for Gaussian random fields allows us to understand the following observed features: (i) the appearance of an exclusion zone at small separation, whose size depends both on rarity and signature (i.e. the number of negative eigenvalues) of the critical points involved; (ii) the amplification of the baryonic acoustic oscillation bump with rarity and its reversal for cross-correlations involving negatively biased critical points; (iii) the orientation-dependent small-separation divergence of the cross-correlations of peaks and filaments (respectively voids and walls) that reflects the relative loci of such points in the filament’s (respectively wall’s) eigenframe. The (cross-) correlations involving the most non-linear critical points (peaks, voids) display significant variation with redshift, while those involving less non-linear critical points seem mostly insensitive to redshift evolution, which should prove advantageous to model. The ratios of distances to the maxima of the peak-to-wall and peak-to-void over that of the peak-to-filament cross-correlation are ${\sim} \sqrt{2}$ and ${\sim} \sqrt{3}$, respectively, which could be interpreted as the cosmic crystal being on average close to a cubic lattice. The insensitivity to redshift evolution suggests that the absolute and relative clustering of critical points could become a topologically robust alternative to standard clustering techniques when analysing upcoming surveys such as Euclid or Large Synoptic Survey Telescope (LSST).
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Buckett, M. I., L. D. Marks, and D. E. Luzzi. "Correlation analysis of structure images." Proceedings, annual meeting, Electron Microscopy Society of America 45 (August 1987): 752–53. http://dx.doi.org/10.1017/s0424820100128079.

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A typical high resolution structure image contains a large amount of intensity information which is masked by both statistical and amorphous noise. One useful method of quantifying such images is to employ correlation techniques. When one seeks to quantify the atom column positions, correlation techniques can be used to decompose the image into separate motifs (of specific peak amplitudes and positions - each motif corresponding to a single column of atoms), thereby reducing the data to a more manageable form.This problem can be considered as the least squares minimization of the function: where I(r) is the image, and m(r) is the motif, and the unknowns are the positions, rj, of the motifs and their peak heights, αj. The standard approach is to look for peaks in the cross-correlation (equation 2) between the motif and image, to determine rj and αj
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Adachi, M., T. Ohshima, S. Yamada, and T. Satoh. "Cross-correlation analysis of taste neuron pairs in rat solitary tract nucleus." Journal of Neurophysiology 62, no. 2 (August 1, 1989): 501–9. http://dx.doi.org/10.1152/jn.1989.62.2.501.

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1. Experiments were conducted to examine the possibility that the taste-sensitive neurons with similar taste-selectivity are preferentially innervated by common driving neurons whose taste-selectivity is also similar. 2. Multiple microelectrodes, in most cases a pair of glued electrodes, were inserted into the unilateral solitary tract nucleus (NTS) of the rat, and simultaneous recordings were made in neuron pairs responding to the four basic taste stimuli. The spike response density (RD) of each neuron during tastant stimulation was determined. Correlation coefficients of spike occurrence were calculated for each neuron pair during application of tastants and distilled water and also during spontaneous background activity. The frequency of correlated discharge (FC) of a neuron pair was measured as the area of the peak appearing on the cross-correlogram (CC). The FC value was divided by the RD value to calculate the weight of the correlated discharges in the output of each neuron (WC value). 3. Eleven pairs showed peaks in the CC constructed during tastant stimulation, whereas in other 11 pairs no peaks were found. The cross-correlation-positive group with peaks was composed of 18 NaCl-best (responding most vigorously to NaCl) and 4 HCl-best neurons, whereas the negative group without peaks included 9 NaCl-best, 9 HCl-best, and 4 sucrose-best neurons. 4. In the cross-correlation-positive pairs the taste quality most effective for one of the component neurons was often (13 NaCl-best and 2 HCl-best, 15/22 = 0.681) identical to the taste quality giving the highest probability of correlated discharge, i.e., highest FC value, in the neuron pair. 5. There were five cross-correlation-positive pairs (5/11 = 0.455) in which both of the component neurons were NaCl-best and the FC value was highest during NaCl stimulation. 6. The CCs constructed during water application exhibited peaks for all the pairs which gave positive cross-correlation in response to stimulation with tastants, whereas all pairs with negative cross-correlation during tastant stimulation never gave a detectable peak during water application. 7. In three pairs of the cross-correlation-positive group, the CCs constructed during spontaneous background activity without application of any liquid showed a small peak. 8. During NaCl stimulation some neurons exhibited relatively high FC values, but the WC values were always low. In contrast, during sucrose stimulation, the FC value was always low, but the WC value was quite high in some neurons.(ABSTRACT TRUNCATED AT 400 WORDS)
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Marigheto, N., L. Venturi, D. Hibberd, K. M. Wright, G. Ferrante, and B. P. Hills. "Methods for peak assignment in low-resolution multidimensional NMR cross-correlation relaxometry." Journal of Magnetic Resonance 187, no. 2 (August 2007): 327–42. http://dx.doi.org/10.1016/j.jmr.2007.04.016.

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Tomás, María-Baralida, Belén Ferrer, and David Mas. "Influence of Neighborhood Size and Cross-Correlation Peak-Fitting Method on Location Accuracy." Sensors 20, no. 22 (November 18, 2020): 6596. http://dx.doi.org/10.3390/s20226596.

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A known technique to obtain subpixel resolution by using object tracking through cross-correlation consists of interpolating the obtained correlation function and then refining peak location. Although the technique provides accurate results, peak location is usually biased toward the closest integer coordinate. This effect is known as the peak-locking error and it strongly limits this calculation technique’s experimental accuracy. This error may differ depending on the scene and algorithm used to fit and interpolate the correlation peak, but in general, it may be attributed to a sampling problem and the presence of aliasing. Many studies in the literature analyze this effect in the Fourier domain. Here, we propose an alternative analysis on the spatial domain. According to our interpretation, the peak-locking error may be produced by a non-symmetrical sample distribution, thus provoking a bias in the result. According to this, the peak interpolant function, the size of the local domain and low-pass filters play a relevant role in diminishing the error. Our study explores these effects on different samples taken from the DIC Challenge database, and the results show that, in general, peak fitting with a Gaussian function on a relatively large domain provides the most accurate results.
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MA, CHUN-WANG, HUI-LING WEI, and YU-QI LI. "THE SYSTEMATIC BEHAVIOR IN THE FRAGMENTS OF THE CALCIUM ISOTOPES PROJECTILE FRAGMENTATION." International Journal of Modern Physics E 19, no. 08n09 (September 2010): 1545–52. http://dx.doi.org/10.1142/s0218301310015941.

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We have calculated the cross sections of the fragments produced in the projectile fragmentation of the even 36–52 Ca isotopes using the statistical abrasion-ablation model. The isospin effect in the projectile fragmentation are studied by investigating the peak positions and the widths of the fragment isotopic cross section distributions. The peak positions of the fragments isotopic cross section distributions have good linear correlation to the Z of the fragments and the correlations are fitted using the linear function. The correlations between slopes b and the binding energies of the neutron ( S n) of the projectile nuclei, the differences between the binding energies of the neutron and proton( S n- S p) of the projectile nuclei and the neutron-skin thickness (δnp) are studied. It is found that b and δnp has a good linear correlation for the neutron-rich projectile nuclei.
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Chaves, C., C. Ibiapina, C. R. Andrade, R. Godinho, C. G. Alvim, and A. A. Cruz. "Correlation between peak nasal inspiratory flow and peak expiratory flow in children and adolescents." Rhinology journal 50, no. 4 (December 1, 2012): 381–85. http://dx.doi.org/10.4193/rhino12.073.

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Background: PEAK nasal inspiratory flow (PNIF) has been proposed as a simple method to evaluate nasal patency. Asthma and allergic rhinitis are commonly associated, and lower airway assessment can provide information concerning an objective interpretation of nasal function. Aims: TO determine whether the PNIF is correlated with peak expiratory flow (PEF) in children and adolescents. Methods and results: Cross-sectional study carried out in healthy students randomly chosen in 14 public schools of the city of Belo Horizonte. PNIF and PEF were assessed for each subject as the following characteristics: gender, height, weight and age. We created a linear regression model to explain the PNIF, in which we included all the variables with a p value ≤ 0.25 in a univariate analysis, and to calculate the relationship between the maximum PNIF and maximum PEF by the Spearman correlation coefficient. In total, 297 healthy subjects, aged between six and eighteen years were evaluated. A positive and significant correlation between PNIF and PEF was found. Conclusions: PEF is predictive of PNIF. However, these measures evaluate two distinct segments of the airways and should be both obtained for a more precise assessment of airflow limitation.
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Dissertations / Theses on the topic "Cross Correlation Peak"

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Srinivasan, Nirmala. "Cross-Correlation Of Biomedical Images Using Two Dimensional Discrete Hermite Functions." University of Akron / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=akron1341866987.

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Book chapters on the topic "Cross Correlation Peak"

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Dai, Xinzhi, Junwei Nie, Baiyu Li, Zukun Lu, and Gang Ou. "Analysis of Cross-Correlation Peak Distortion Caused by Antenna Array Space-Time Adaptive Processing." In China Satellite Navigation Conference (CSNC) 2017 Proceedings: Volume I, 821–31. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4588-2_68.

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Lee, Sangwon, Byeolteo Park, Youngjai Kim, and Hyun Myung. "Peak Detection with Pile-Up Rejection Using Multiple-Template Cross-Correlation for MWD (Measurement While Drilling)." In Advances in Intelligent Systems and Computing, 753–58. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16841-8_68.

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Hattori, Masazumi, Ilhyock Shim, and Yoshihiko Sugihara. "Volatility Contagion across the Equity Markets of Developed and Emerging Market Economies." In Macroeconomic Shocks and Unconventional Monetary Policy, 99–117. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198838104.003.0005.

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Using variance risk premiums (VRPs) nonparametrically calculated from equity markets in selected major developed economies and emerging market economies (EMEs) over 2007–15, this chapter documents the correlation of VRPs across markets, examining whether equity fund flows work as a path through which VRPs spill over globally. It finds that VRPs tend to spike up during market turmoil such as the peak of the global financial crisis and the European debt crisis; that all cross-equity market correlations of VRPs are positive, and that some economy pairs exhibit high levels of the correlation. In terms of volatility contagion, it finds that an increase in US VRPs significantly reduces equity fund flows to other developed economies, but not those to EMEs, following the global financial crisis. Two-stage least squares estimation results show that equity fund flows are a channel for spillover of US VRPs to VRPs in other developed economies.
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"Findings and Analysis." In Achieving Peak Sales Performance for Optimal Business Value and Sustainability, 273–319. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1639-3.ch005.

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This chapter presents the results of the data analysis. The data was collected and processed in accordance to the problems posed at the outset of this research, which was to understand which determinants impacted on SPP. The results of both the quantitative and qualitative data are presented in this chapter. The quantitative data analysis comprises of descriptive analysis, cross-tabulation, regression analysis, and correlation analysis. SPSS, a commercially available statistical software package, was used to perform the analysis. In addition, this chapter also reports the findings of the qualitative data analysis where the key themes were noted. The findings are structured in line with the literature review: organisational determinants, personal determinants, and symbiotic determinants. The data is presented in both quantitative (numerical) and qualitative (non-numerical) formats, as per the selected research methodology.
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Chae, K., S. Woo, S. Yoon, S. Yoo, S. Kim, G. Jee, H. Liu, and D. Yeom. "A generating scheme of a side-peak-free correlation function for TMBOC(6,1,4/33) signal tracking based on cross-correlations." In Applied System Innovation, 75–78. CRC Press, 2016. http://dx.doi.org/10.1201/b21811-18.

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Malik, Sunesh, Rama Kishore Reddlapalli, and Girdhar Gopal. "GA-Based Optimized Image Watermarking Method With Histogram and Butterworth Filtering." In Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms, 851–73. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8048-6.ch043.

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The present paper proposes a new and significant method of optimization for digital image watermarking by using a combination of Genetic Algorithms (GA), Histogram and Butterworth filtering. In this proposed method, the histogram range selection of low frequency components is taken as a significant parameter which assists in bettering the imperceptibility and robustness against attacks. The tradeoff between the perceptual transparency and robustness is considered as an optimization puzzle which is solved with the help of Genetic Algorithm. As a result, the experimental outcomes of the present approach are obtained. These results are secure and robust to various attacks such as rotation, cropping, scaling, additive noise and filtering attacks. The peak signal to noise ratio (PSNR) and Normalized cross correlation (NC) are carefully analyzed and assessed for a set of images and MATLAB2016B software is employed as a means of accomplishing or achieving these experimental results.
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Conference papers on the topic "Cross Correlation Peak"

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Robinson, Mitchell B., Stefan Carp, Adriano Peruch, Nisan Ozana, and Maria Franceschini. "Continuous wave diffuse correlation spectroscopy beyond the water peak enabled by InGaAs SPAD cross correlation." In Neural Imaging and Sensing 2021, edited by Qingming Luo, Jun Ding, and Ling Fu. SPIE, 2021. http://dx.doi.org/10.1117/12.2578914.

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Young, C. N., R. Gilbert, D. A. Johnson, and E. J. Weckman. "Vector Positioning for Cross Correlation PIV." In ASME 2002 Joint U.S.-European Fluids Engineering Division Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/fedsm2002-31171.

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Continuing advances in digital imaging technology stimulate greater interest in applying particle image velocimetry (PIV) over increasingly larger fields of view. Unfortunately when larger fields of view are analyzed, velocity gradients in the image become more localized. In addition, non-uniformities in image illumination and particle number density become more prevalent. These factors, coupled with the requirement that large areas of interest (AOIs) must be employed to measure the full range of velocity, cause degradation of correlation results (i.e. broadening and/or splintering of the cross correlation peak) which leads to positional bias errors in the measured velocity field. More advanced super resolution strategies that employ an iterative AOI reduction process inherently reduce positional bias in PIV results but these strategies can break down in complex flows where velocity gradients are steep and particle dispersion does not remain uniformly random. To mitigate these problems a simple but effective technique is presented that enables individual velocity vectors to be placed within an AOI at locations toward which the cross correlation plane is biased. The method involves analysis of the correlation plane to extract the dominant features that are matched in two successive AOIs. To demonstrate the utility of the methodology results obtained from synthetic images are compared against results obtained using the conventional PIV approach.
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Charonko, John J., and Pavlos P. Vlachos. "Estimation of Uncertainty Bounds From Cross Correlation Peak Ratio for Individual PIV Measurements." In ASME 2012 Fluids Engineering Division Summer Meeting collocated with the ASME 2012 Heat Transfer Summer Conference and the ASME 2012 10th International Conference on Nanochannels, Microchannels, and Minichannels. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/fedsm2012-72475.

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Numerous studies have established firmly that particle image velocimetry (PIV) is a robust method for non-invasive, quantitative measurements of fluid velocity, and that when carefully conducted, typical measurements can accurately detect displacements in digital images with a resolution well below a single pixel (in some cases well below a hundredth of a pixel). However, previously these estimates have only been able to provide guidance on the expected error for an average measurement under specific image quality and flow conditions. This paper demonstrates a new method for estimating the uncertainty bounds to within a given confidence interval for a specific, individual measurement. Here, the ratio of primary to secondary peak heights in a phase-only generalized cross-correlation is shown to correlate strongly with the range of observed error values for a given measurement, regardless of flow condition or image quality. Using an analytical model of the relationship derived from synthetic data sets, the uncertainty bounds at a 95% confidence interval are then computed for several artificial and experimental flow fields, and the resulting errors are shown to match closely to the predicted uncertainties. While this method stops short of being able to predict the true error for a given measurement, knowledge of the uncertainty level for a PIV experiment should provide great benefits when applying the results of PIV analysis to engineering design studies and CFD (computational fluid dynamics) validation efforts.
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Kazemian, Mohsen, Pooria Varahram, Shaiful Jahari B. Hashim, Borhanuddin B. Mohd Ali, Somayeh Mohammady, and Nasri Sulaiman. "Peak-to-average power ratio reduction based on Cross-Correlation in OFDM systems." In 2014 16th International Conference on Advanced Communication Technology (ICACT). Global IT Research Institute (GIRI), 2014. http://dx.doi.org/10.1109/icact.2014.6778957.

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Chen, Jun, and Joseph Katz. "A Correlation Mapping Method to Eliminate the Peak-Locking Effect in PIV Analysis." In ASME 2004 Heat Transfer/Fluids Engineering Summer Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/ht-fed2004-56400.

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“Peak-locking” causes deterministic mean measurement bias in most of the existing cross-correlation based algorithms for PIV data analysis. This phenomenon is inherent to the typical smooth curve-fitting through discrete correlation values which are used to obtain the sub-pixel accuracy in velocity. In this paper we introduce a new algorithm/method for obtaining the sub-pixel accuracy, which eliminates the peak-locking effect. We refer to this procedure as “correlation mapping method”. In an ideal case, the second exposure (image 2) in a PIV measurement can be regarded as a mapping of the first exposure (image 1) where the mapping rules are affected by displacement, deformation, out of plane motion, etc. The correlation mapping method is based on shifting of image 1 by certain sub-pixel value, thus generating a virtual image (2′), whose gray level can be expressed in terms of the original image and the sub-pixel displacement. Thus, the correlation map of images 1 and 2′ is also a function of the intensity distribution in image 1 and the displacement. This correlation map is matched with the measured correlation map of images 1 and 2, providing a system of equations, one for discrete point in the correlation map with the sub-pixel values as unknowns. Solving these equations for each point in the vicinity of the correlation peak generates a series of sub-pixel displacements. Least square fitting is then used to determine the sub-pixel displacement with minimal difference between the real and virtual correlation values. This method is applied to several experimental and synthetic flow image pairs. In most cases the results show substantial improvements in sub-pixel accuracy in comparison to other algorithms and it eliminates the peak locking bias.
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Rhudy, Matthew, Brian Bucci, Jeffrey Vipperman, Jeffrey Allanach, and Bruce Abraham. "Microphone Array Analysis Methods Using Cross-Correlations." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-10798.

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Due to civilian noise complaints and damage claims, there is a need to establish an accurate record of impulse noise generated at military installations. Current noise monitoring systems are susceptible to false positive detection of impulse events due to wind noise. In order to analyze the characteristics of noise events, multiple channel data methods were investigated. A microphone array was used to collect four channel data of military impulse noise and wind noise. These data were then analyzed using cross-correlation functions to characterize the input waveforms. Four different analyses of microphone array data are presented. A new value, the min peak correlation coefficient, is defined as a measure of the likelihood that a given waveform originated from a correlated noise source. Using a sound source localization technique, the angle of incidence of the noise source can be calculated. A method was also developed to combine the four individual microphone channels into one. This method aimed to preserve the correlated part of the overall signal, while minimizing the effects of uncorrelated noise, such as wind. Lastly, a statistical method called the acoustic likelihood test is presented as a method of determining if a signal is correlated or not.
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Nishihara, Takashi, Fumio Inada, Akira Yasuo, Ryo Morita, Akihiro Sakashita, and Jun Mizutani. "Turbulence-Induced Fluid Dynamic Forces Acting on Cross-Shaped Tube Bundle in Cross Flow." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-32758.

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A cross-shaped tube bundle with dense arrangement may be designed for a lower plenum structure in a next generation LWR, though the characteristics of flow-induced vibration of this type of tube bundle remain virtually unknown. In this study, turbulence-induced fluid dynamic forces acting on a cross-shaped tube bundle with a dense arrangement subject to cross flow were measured by water tunnel tests with two types of scale models. One is a small-scale model to measure local fluid dynamic forces and their correlation length in the lift and drag direction. The other is a large-scale model to investigate the effect of the Reynolds number on fluid dynamic forces in the lift, drag and torsional directions. Free oscillation tests with another small-scale model were also conducted to measure vibration amplitude by random excitation force. In conclusion, the following results were obtained. Vortex-induced vibration cannot arise in the cross-shaped tube bundle, since a typical peak corresponding to periodic vortex shedding was not observed in power spectral density for fluid excitation force. Power spectral densities of fluid dynamic forces in the drag, lift and torsional directions have mutually similar properties and they are hardly dependent on the Reynolds number. The experimental results were compiled into dimensionless correlation equations composed of the power spectral density for the local fluid excitation force and its correlation length. They are useful for evaluating the random vibration amplitude. The estimated amplitudes of turbulence-induced vibration by the correlation equation coincide with those of the experimental results obtained by the free-oscillation tests.
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Shoji, Kota, and Satoki Ogiso. "Evaluation of Non-Line-Of-Sight Based on Peak to RMS Ratio of Cross-Correlation Function Between Two Microphones." In 2019 IEEE 8th Global Conference on Consumer Electronics (GCCE). IEEE, 2019. http://dx.doi.org/10.1109/gcce46687.2019.9015215.

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Chen, Jun, and Joseph Katz. "Advances of the Correlation Mapping Method to Eliminate the Peak-Locking Effect in PIV Analysis." In ASME 2005 Fluids Engineering Division Summer Meeting. ASMEDC, 2005. http://dx.doi.org/10.1115/fedsm2005-77437.

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The Peak-locking effect causes mean bias in most of the existing correlation based algorithms for PIV data analysis. This phenomenon is inherent to the Sub-pixel Curve Fitting (SPCF) through discrete correlation values, which is used to obtain the sub-pixel part of the displacement. A new technique for obtaining sub-pixel accuracy, the Correlation Mapping Method (CMM), was proposed by Chen & Katz [1, 2]. This new method works effectively and the peak-locking disappears in all the previous test cases, including applying to both synthetic and experimental images. The random errors are also significantly reduced. In this paper, an optimization of the algorithm is reported. Using sub-pixel interpolation, the cross-correlation function between image 1 and image 2 is expressed as a polynomial function with unknown displacement, in which the coefficients are determined by the autocorrelation function of the image 1. This virtual correlation function can be matched with the exact correlation value at every point in the vicinity of the discrete correlation peak (a 5×5 pixels area is chosen in the present study). A least square method is used to find the optimal displacement components that minimize the difference between the real and virtual correlation values. The performances of this method at the presence of background noise and out-of-plane motion are investigated by using synthetic images, as well as the influence of under-resolved particle images, and compared with the result of the SPCF method. The advantage of the CMM over SPCF is demonstrated in these studies.
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Ergin, F. Go¨khan, Bo Beltoft Watz, Kaspars Erglis, and Andrejs Cebers. "Poor-Contrast Particle Image Processing in Microscale Mixing." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-24900.

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Particle image velocimetry (PIV) often employs the cross-correlation function to identify average particle displacement in an interrogation window. The quality of correlation peak has a strong dependence on the signal-to-noise ratio (SNR), or contrast of the particle images. In fact, variable-contrast particle images are not uncommon in the PIV community: Strong light sheet intensity variations, wall reflections, multiple scattering in densely-seeded regions and two-phase flow applications are likely sources of local contrast variations. In this paper, we choose an image pair obtained in a micro-scale mixing experiment with severe local contrast gradients. In regions where image contrast is sufficiently poor, the noise peaks cast a shadow on the true correlation peak, producing erroneous velocity vectors. This work aims to demonstrate that two image pre-processing techniques — local contrast normalization and Difference of Gaussian (DoG) filter — improve the correlation results significantly in poor-contrast regions.
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