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Journal articles on the topic 'Distribution of frequency'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 February 2022

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1

Rana, Shilpesh C., Gaurang I. Joshi, and Dr N. J. Shrimali Dr. N. J. Shrimali. "Flood Frequency Study For Kadana Reservoir Projectby Gumbel’s Frequency Distribution Method." Indian Journal of Applied Research 4, no. 1 (October 1, 2011): 213–16. http://dx.doi.org/10.15373/2249555x/jan2014/63.

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2

Manikandan, S. "Frequency distribution." Journal of Pharmacology and Pharmacotherapeutics 2, no. 1 (2011): 54. http://dx.doi.org/10.4103/0976-500x.77120.

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3

Davanger, Martin, Amund Ringvold, Sigmund Blika, and Tor Elsås. "Frequency distribution of IOP." Acta Ophthalmologica 69, no. 5 (May 27, 2009): 561–64. http://dx.doi.org/10.1111/j.1755-3768.1991.tb04839.x.

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4

Pei, Soo Chang, and Er Jung Tsai. "New Time-Frequency Distribution." Circuits, Systems, and Signal Processing 14, no. 4 (July 1995): 539–53. http://dx.doi.org/10.1007/bf01260336.

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5

SUN, Shuping, Zhongwei JIANG, and Haibin WANG. "1204 Heart Sound Clustering Method Using Time-Frequency Distribution Energy." Proceedings of Conference of Chugoku-Shikoku Branch 2010.48 (2010): 365–66. http://dx.doi.org/10.1299/jsmecs.2010.48.365.

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6

Stankovic, L. J., and S. Stankovic. "An analysis of instantaneous frequency representation using time-frequency distributions-generalized Wigner distribution." IEEE Transactions on Signal Processing 43, no. 2 (1995): 549–52. http://dx.doi.org/10.1109/78.348139.

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7

Řehák, Jan. "Variability of Spatial Frequency Distribution." Geografie 95, no. 3 (1990): 186–94. http://dx.doi.org/10.37040/geografie1990095030186.

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A measure of spatial variability (called geostructural variance) is defined for a frequency distribution on a finite set of places in a space whose geographical relations are assessed by a matrix of (generally conceived) distances. A set of measures stemming from the same approach describe the positions and properties of individual places in the geostructure. This complex of characteristics provides a clear-cut way of an analytical diagnostic reflection of the spatial properties of frequency distributions.

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8

Powell, Eric N. "Use of commercial vessels in survey augmentation: the size-frequency distribution." Scientia Marina 70, no. 3 (September 30, 2006): 519–44. http://dx.doi.org/10.3989/scimar.2006.70n3519.

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9

Kato, Mamoru. "Frequency Distribution of Felt Earthquakes." Bulletin of the Seismological Society of America 103, no. 1 (February 2013): 606–10. http://dx.doi.org/10.1785/0120120193.

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10

Robinson, D., E. A. Bevan, and C. D. Ritchie. "FREQUENCY DISTRIBUTION OF SERUM CHOLESTEROL." Lancet 333, no. 8644 (April 1989): 965. http://dx.doi.org/10.1016/s0140-6736(89)92554-3.

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11

Bloch, Matthieu, Steven W. McLaughlin, Jean-Marc Merolla, and Frédéric Patois. "Frequency-coded quantum key distribution." Optics Letters 32, no. 3 (January 12, 2007): 301. http://dx.doi.org/10.1364/ol.32.000301.

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12

Cohen, L., and T. Posch. "Positive time-frequency distribution functions." IEEE Transactions on Acoustics, Speech, and Signal Processing 33, no. 1 (February 1985): 31–38. http://dx.doi.org/10.1109/tassp.1985.1164512.

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13

BENJAMIN, L. R., and R. C. HARDWICK. "Statistics of the frequency distribution." Annals of Botany 58, no. 6 (December 1986): 758–59. http://dx.doi.org/10.1093/oxfordjournals.aob.a087241.

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14

BENJAMIN, L. R., and R. C. HARDWICK. "Moments of the frequency distribution." Annals of Botany 58, no. 6 (December 1986): 761. http://dx.doi.org/10.1093/oxfordjournals.aob.a087246.

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15

Abaimov, S. G., K. F. Tiampo, D. L. Turcotte, and J. B. Rundle. "Recurrent frequency-size distribution of characteristic events." Nonlinear Processes in Geophysics 16, no. 2 (April 28, 2009): 333–50. http://dx.doi.org/10.5194/npg-16-333-2009.

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Abstract. Statistical frequency-size (frequency-magnitude) properties of earthquake occurrence play an important role in seismic hazard assessments. The behavior of earthquakes is represented by two different statistics: interoccurrent behavior in a region and recurrent behavior at a given point on a fault (or at a given fault). The interoccurrent frequency-size behavior has been investigated by many authors and generally obeys the power-law Gutenberg-Richter distribution to a good approximation. It is expected that the recurrent frequency-size behavior should obey different statistics. However, this problem has received little attention because historic earthquake sequences do not contain enough events to reconstruct the necessary statistics. To overcome this lack of data, this paper investigates the recurrent frequency-size behavior for several problems. First, the sequences of creep events on a creeping section of the San Andreas fault are investigated. The applicability of the Brownian passage-time, lognormal, and Weibull distributions to the recurrent frequency-size statistics of slip events is tested and the Weibull distribution is found to be the best-fit distribution. To verify this result the behaviors of numerical slider-block and sand-pile models are investigated and the Weibull distribution is confirmed as the applicable distribution for these models as well. Exponents β of the best-fit Weibull distributions for the observed creep event sequences and for the slider-block model are found to have similar values ranging from 1.6 to 2.2 with the corresponding aperiodicities CV of the applied distribution ranging from 0.47 to 0.64. We also note similarities between recurrent time-interval statistics and recurrent frequency-size statistics.

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16

Wang, Chenshu, and Moeness G. Amin. "Time–frequency distribution spectral polynomials for instantanous frequency estimation." Signal Processing 76, no. 2 (July 1999): 211–17. http://dx.doi.org/10.1016/s0165-1684(99)00009-2.

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17

Stankovic, L. "A time-frequency distribution concentrated along the instantaneous frequency." IEEE Signal Processing Letters 3, no. 3 (March 1996): 89–91. http://dx.doi.org/10.1109/97.481164.

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18

Neave, Edwin H. "A Frequency Distribution Method for Valuing Average Options." ASTIN Bulletin 27, no. 2 (November 1997): 173–205. http://dx.doi.org/10.2143/ast.27.2.542047.

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AbstractThis paper finds payoff frequency distributions for valuing European and American fixed strike average options on a discrete time, recombining multiplicative binomial asset price process. In comparison to other discrete valuation methods the distributions, obtained analytically from a generating function, greatly reduce the computational requirements needed for accurate valuation. Less data are needed to value geometric than arithmetic averages, but the magnitude of calculations is similar for both instruments. Calculations of orderT3are needed to value European instruments, of orderT4to value their American counterparts. A frequency distribution of a quantity calledpath sumsis used to value geometric average options, and a joint distribution of path sums and realized prices is used to value arithmetic average options. The frequency distributions give an exact value for geometric average, an approximate value for arithmetic average instruments. The method obtains additional information from the generating function to estimate approximation errors relative to the exact binomial solution. If the errors are significant they can be reduced using still further detail from the generating function. Error reduction can be performed selectively to minimize additional calculation.

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19

SOMIYA, Satoshi, Tetsu ASANO, and Taku SUGIYAMA. "Relationship between Frequency Distribution Characteristics of Acoustic Emission and Fracture Mechanisms on AFRP (2nd Report, Analysis of Frequency Distribution by Weighted Mean Frequency Distribution Method)." Transactions of the Japan Society of Mechanical Engineers Series A 62, no. 598 (1996): 1376–81. http://dx.doi.org/10.1299/kikaia.62.1376.

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20

Liu, Shu Lin, Xian Ming Wang, Hui Wang, and Hai Feng Zhao. "Extension of Traditional Frequency and Research on Time-Frequency Distribution." Applied Mechanics and Materials 44-47 (December 2010): 2089–93. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.2089.

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The concept of traditional frequency is extended and the concept of local frequency is proposed, which makes the physical meaning of frequency clearer. The wide adaptability of local frequency is also discussed. Moreover, a novel time-frequency analysis method is presented based on local frequency. The time-frequency distribution of continuous triangular wave signal is analyzed by the novel approach. Compared with wavelet transform and Hilbert-Huang transform (HHT), the results show that the concept of local frequency is correct and the novel time-frequency approach is effective.

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21

Mizutani, Shinjiro. "Bed-thickness and its frequency distribution." Journal of the Sedimentological Society of Japan 75, no. 1 (2016): 17–24. http://dx.doi.org/10.4096/jssj.75.17.

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22

Aslam, Nighat, Khalid Nadeem Asif, Sadia Zafar, and Amer Jamil. "HCV infection and frequency of distribution." Professional Medical Journal 26, no. 10 (October 10, 2019): 1770–75. http://dx.doi.org/10.29309/tpmj/2019.26.10.4139.

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Worldwide, an estimated 130-170 million people are infected with Hepatitis C. The geographic distribution of HCV infection is highly variable between and within countries. To start the antiviral therapy, it is necessary to find the genotype in order to get better forecast about observed duration of treatment. This also provides the load of virus. Treatments for patients with chronic HCV infection have recently advanced with newly licensed antivirals, which specifically target HCV. Objectives: To find out the prevalence of HCV in Faisalabad region of Pakistan and to evaluate the frequency distribution of various HCV genotypes among those with HCV infection. Study Design: Descriptive cross sectional. Settings: Blood samples were received from Biotech Lab, Pinum cancer hospital Faisal Laboratory, Alshafa lab Jaranwala, Mehran Lab, Samundari, Rashid Lab, Shahkot and Molecular care, Human Molecular Diagnostic Department of Biochemistry University of Agriculture Faisalabad. Period: May 2016 to April 2017. Material and Methods: The data for this study included a total of 382 anti-HCV positive blood sera samples, collected from different collection centers. Nested reverse transcription (RT) PCR was done for the qualitative detection of HCV. RNA using primers that correspond to the relatively conservative 5'UTR noncoding region of the highly mutable HCV were used. Data was analysed using the descriptive statistics. Results: 233 samples were found to be confirm positive for HCV RNA by qualitative PCR. 98 (42%) were females and 135 (58%) were males. The age-group of 36-45 years bear the largest number of HCV patients (37.08%) and smallest number of patients was in the 56-65 years age-group. A total of 87.55% patients belong were below 45 years of age. The genotype 3a, 135 (77%) was the most prevalent form of all HCV genotypes in Faisalabad. A peripheral area of Faisalabad almost same distribution has been observed. The other strains detected were 2a, 29% 3b 11% were males and 5% were female), and none of the patient was detected with 2b, 4a, 5a and 6a genotype of HCV. Conclusion: This data analysis shows that there is no specific relationship of age-groups or genders in case of prevalence of different HCV Genotypes but female patients were found to have higher frequency of HCV infection.

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23

Xiaoxi Hu, Gang Luo, Yongjing Lu, and Lingyun Xiang. "A Steganography on Synonym Frequency Distribution." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 5, no. 10 (May 31, 2013): 206–14. http://dx.doi.org/10.4156/aiss.vol5.issue10.24.

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24

Lu, Yao, Peng Zhang, Yanan Cao, Yue Hu, and Li Guo. "On the Frequency Distribution of Retweets." Procedia Computer Science 31 (2014): 747–53. http://dx.doi.org/10.1016/j.procs.2014.05.323.

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25

Dicle, Mehmet F., and Betul Dicle. "Content Analysis: Frequency Distribution of Words." Stata Journal: Promoting communications on statistics and Stata 18, no. 2 (June 2018): 379–86. http://dx.doi.org/10.1177/1536867x1801800205.

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Many academic fields use content analysis. At the core of most common content analysis lies frequency distribution of individual words. Websites and documents are mined for usage and frequency of certain words. In this article, we introduce a community-contributed command, wordfreq, to process content (online and local) and to prepare a frequency distribution of individual words. Additionally, another community-contributed command, wordcloud, is introduced to draw a simple word cloud graph for visual analysis of the frequent usage of specific words.

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26

Diethorn, E. J. "The generalized exponential time-frequency distribution." IEEE Transactions on Signal Processing 42, no. 5 (May 1994): 1028–37. http://dx.doi.org/10.1109/78.295214.

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27

Hearon, S. B., and M. G. Amin. "Minimum-variance time-frequency distribution kernels." IEEE Transactions on Signal Processing 43, no. 5 (May 1995): 1258–62. http://dx.doi.org/10.1109/78.382412.

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28

Rocca, Walter A., and Emre Kokmen. "Frequency and Distribution of Vascular Dementia." Alzheimer Disease & Associated Disorders 13, Supplement (December 1999): S9–14. http://dx.doi.org/10.1097/00002093-199912001-00003.

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29

Rocca, Walter A., and Emre Kokmen. "Frequency and Distribution of Vascular Dementia." Alzheimer Disease & Associated Disorders 13, Supplement 3 (December 1999): S9—S14. http://dx.doi.org/10.1097/00002093-199912003-00003.

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30

Wei, Ling Y., and Peter Chow. "Frequency Distribution of Human Pulse Spectra." IEEE Transactions on Biomedical Engineering BME-32, no. 3 (March 1985): 245–46. http://dx.doi.org/10.1109/tbme.1985.325537.

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31

KOTHYARI, U. C. "Frequency distribution of river bed materials." Sedimentology 42, no. 2 (April 1995): 283–89. http://dx.doi.org/10.1111/j.1365-3091.1995.tb02103.x.

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32

Salim, Imad, Anthony Igwe, Jerry Brown, James Sherrill, Tarun Sonkhya, and Anass Jerrari. "Seasonal Precipitation Frequency and Distribution Analysis." Proceedings of the Water Environment Federation 2011, no. 5 (January 1, 2011): 479–92. http://dx.doi.org/10.2175/193864711802837679.

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33

Levine, Judah. "Time and frequency distribution using satellites." Reports on Progress in Physics 65, no. 8 (July 10, 2002): 1119–64. http://dx.doi.org/10.1088/0034-4885/65/8/201.

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34

Brooks, C. E. "The frequency distribution of hailstone sizes." Quarterly Journal of the Royal Meteorological Society 70, no. 305 (July 20, 2009): 227–28. http://dx.doi.org/10.1002/qj.49707030512.

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35

Parker, R. S., and Brent M. Troutman. "Frequency distribution for suspended sediment loads." Water Resources Research 25, no. 7 (July 1989): 1567–74. http://dx.doi.org/10.1029/wr025i007p01567.

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36

Robinson, P. J., and D. R. Easterling. "The Frequency Distribution of Thunderstorm Durations." Journal of Applied Meteorology 27, no. 1 (January 1988): 77–82. http://dx.doi.org/10.1175/1520-0450(1988)027<0077:tfdotd>2.0.co;2.

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37

Ejiri, Koichi, Niklaus Staeheli, and Shiori Ooaku. "Word frequency distribution in Japanese text*." Journal of Quantitative Linguistics 1, no. 3 (January 1994): 212–23. http://dx.doi.org/10.1080/09296179408590019.

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38

Janssen, A. J. E. M. "Positivity of time-frequency distribution functions." Signal Processing 14, no. 3 (April 1988): 243–52. http://dx.doi.org/10.1016/0165-1684(88)90079-5.

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39

Kulandai, Arockia David Roy. "Frequency Distribution Fitting for Electronic Documents." International Journal of Applied Sciences and Smart Technologies 03, no. 01 (June 21, 2021): 1–10. http://dx.doi.org/10.24071/ijasst.v3i1.2854.

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Studies of frequency distributions of natural language elements have identified some distributions that offer a good fit. Using electronic documents, we show that some of these distributions cannot be used to model the frequency of bytes in electronic documents even if these documents represent natural language documents.

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40

Yue, Sheng. "A Bivariate Extreme Value Distribution Applied to Flood Frequency Analysis." Hydrology Research 32, no. 1 (February 1, 2001): 49–64. http://dx.doi.org/10.2166/nh.2001.0004.

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This article presents a procedure for use of the Gumbel logistic model to represent the joint distribution of two correlated extreme events. Parameters of the distribution are estimated using the method of moments. On the basis of marginal distributions, the joint distribution, the conditional distributions, and the associated return periods can be deduced. The applicability of the model is demonstrated by using multiple episodic flood events of the Harricana River basin in the province of Quebec, Canada. It is concluded that the model is useful for describing joint probabilistic behavior of multivariate flood events.

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41

Iwahashi, Junko, Shiaki Watanabe, and Takahiko Furuya. "Mean slope-angle frequency distribution and size frequency distribution of landslide masses in Higashikubiki area, Japan." Geomorphology 50, no. 4 (March 2003): 349–64. http://dx.doi.org/10.1016/s0169-555x(02)00222-2.

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42

Werner, S. "The Near-Earth Asteroid Size–Frequency Distribution: A Snapshot of the Lunar Impactor Size–Frequency Distribution." Icarus 156, no. 1 (March 2002): 287–90. http://dx.doi.org/10.1006/icar.2001.6789.

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43

Kwiatkowska, Anna J., and Ewa Symonides. "Statistical analysis of the phytocoenose homogeneity. II. Species frequency distribution and frequency distribution of the standing biomass as a function of the area size." Acta Societatis Botanicorum Poloniae 54, no. 4 (2014): 465–75. http://dx.doi.org/10.5586/asbp.1985.040.

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Homogeneity of the <em>Leucobryo-Pineium</em> phytocoenose was assessed on the grounds of the species frequency distribution and frequency distributions of the total ground-layer biomass and those of individual species. It was confirmed that: 1) species frequency distribution and frequency distribution of biomass, as well as their statistical characteristics depended on the area size and 2) for analysed phytocoenose the area at which frequency distributions of both measures were symmetrical could be determined. The studies showed that phytocoenose homogeneity was related only to the definite area size, i.e. to the definite scale of its spatial differentiation.

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44

Si, Xiaolian. "Higher Order Character Frequency Distribution in Modern Chinese Texts: Application of Zipf's Law." International Journal of Languages, Literature and Linguistics 4, no. 4 (December 2018): 272–75. http://dx.doi.org/10.18178/ijlll.2018.4.4.186.

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45

Wang, Feng, Li Zhong Wang, Shun Lai Zang, De Hong Yu, Chao Yu, and Yu Jiao. "High-Frequency Microwave Heating Technology for Automobile Windshield." Advanced Materials Research 287-290 (July 2011): 2221–24. http://dx.doi.org/10.4028/www.scientific.net/amr.287-290.2221.

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In the paper, a new type of high-frequency microwave heating method for windshield forming process was investigated. In order to obtain the effects of forming process parameters and windshield properties on the forming qualities of windshield, the distributions of electromagnetic energy and temperature were simulated by coupling electromagnetic analysis with multi-physics analysis. Moreover, the influence of different microwave input frequencies on electromagnetic energy and temperature distributions was analyzed. The results show that a travelling-standing wave distribution of electromagnetic energy is formed within windshield. And the temperature distribution and heating time are determined by combined influences of windshield properties and microwave frequency. And the necessary temperature distribution can be realized by electing appropriate microwave frequency.

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46

Li, Man, and Zhi Gang Zhang. "Birthday Distribution Problems." Applied Mechanics and Materials 373-375 (August 2013): 1900–1905. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.1900.

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Based on the distinguishable ball-into-box issue, this paper started from a seemingly simple ball and extended to the question of birthday frequency distribution, i.e. people birthday in different dates probability distribution and the distribution law. In addition, the value was obtained by Monte Carlo simulations with different frequency distribution birthday days, finally when frequency simulation is large, achieving the theoretical value of the frequency values to estimate the probability,and the corresponding distribution can be obtained.

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47

Leščešen, Igor, and Dragan Dolinaj. "Regional Flood Frequency Analysis of the Pannonian Basin." Water 11, no. 2 (January 23, 2019): 193. http://dx.doi.org/10.3390/w11020193.

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In this paper, we performed Regional Flood Frequency Analysis (RFFA) by using L-moments and Annual Maximum Series (AMS) methods. Time series of volumes and duration of floods were derived using the threshold level method for 22 hydrological stations in the Pannonian Basin. For flood definition, a threshold set at Q10 was used. The aim of this research is to derive best-fit regional distribution for the four major rivers within the Pannonian Basin and to provide reliable prediction of flood quantiles. The results show that the investigated area can be considered homogeneous (Vi < 1) both for flood volumes (0.097) and durations (0.074). To determine the best-fit regional distribution, the six most commonly used distributions were used. Results obtained by L-moment ratio diagram and Z statistics show that all distributions satisfy the test criteria, but because the Log-Normal distribution has the value closest to zero, it can be selected as the best-fit distribution for the volumes (0.12) and durations (0.25) of floods.

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48

Loganathan, G. V., C. Y. Kuo, and T. C. McCormick. "Frequency Analysis of Low Flows." Hydrology Research 16, no. 2 (April 1, 1985): 105–28. http://dx.doi.org/10.2166/nh.1985.0009.

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The transformations (i) SMEMAX (ii) Modified SMEMAX (iii) Power and Probability Distributions (iv) Weibull (α,β,γ) or Extreme value type III (v) Weibull (α,β,0) (vi) Log Pearson Type III (vii) Log Boughton are considered for the low flow analysis. Also, different parameter estimating procedures are considered. Both the Weibull and log Pearson can have positive lower bounds and thus their use in fitting low flow probabilities may not be physically justifiable. A new derivation generalizing the SMEMAX transformation is proposed. A new estimator for the log Boughton distribution is presented. It is found that the Boughton distribution with Cunnane's plotting position provides a good fit to low flows for Virginia streams.

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49

Zheng, G. T., and P. D. McFadden. "A Time-Frequency Distribution for Analysis of Signals with Transient Components and Its Application to Vibration Analysis." Journal of Vibration and Acoustics 121, no. 3 (July 1, 1999): 328–33. http://dx.doi.org/10.1115/1.2893984.

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Bilinear time-frequency distributions, which provide simultaneous high resolution in both time and frequency domains, offer advantages for the analysis of vibration signals where the harmonic components and sidebands may be closely spaced. However, the Choi-Williams exponential distribution is found to be unsuitable, and aliasing produced by distributions of the Cohen class also causes problems. An aliasfree exponential time-frequency distribution is introduced, which combines features of distributions of the Cohen class and the generalized Wigner distribution. The new distribution is shown to be well suited to the analysis of signals with transient components.

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50

BEVERIDGE, ANDREW, and LÁSZLÓ LOVÁSZ. "Exit Frequency Matrices for Finite Markov Chains." Combinatorics, Probability and Computing 19, no. 4 (May 14, 2010): 541–60. http://dx.doi.org/10.1017/s0963548310000118.

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Consider a finite irreducible Markov chain on state spaceSwith transition matrixMand stationary distribution π. LetRbe the diagonal matrix of return times,Rii= 1/πi. Given distributions σ, τ andk∈S, the exit frequencyxk(σ, τ) denotes the expected number of times a random walk exits statekbefore an optimal stopping rule from σ to τ halts the walk. For a target distribution τ, we defineXτas then×nmatrix given by (Xτ)ij=xj(i, τ), whereialso denotes the singleton distribution on statei.The dual Markov chain with transition matrix=RM⊤R−1is called thereverse chain. We prove that Markov chain duality extends to matrices of exit frequencies. Specifically, for each target distribution τ, we associate a unique dual distribution τ*. Let$\rX_{\fc{\t}}$denote the matrix of exit frequencies from singletons to τ* on the reverse chain. We show that$\rX_{\fc{\t}} = R (X_{\t}^{\top} - \vb^{\top} \one)R^{-1}$, wherebis a non-negative constant vector (depending on τ). We explore this exit frequency duality and further illuminate the relationship between stopping rules on the original chain and reverse chain.

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