Relevant bibliographies by topics / Sample rate

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Sample rate'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Sample rate"

1

Van Den Enden, Adrianus Wilhelmus Maria. "Sample rate converter." Journal of the Acoustical Society of America 113, no. 2 (2003): 694. http://dx.doi.org/10.1121/1.1560289.

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Choi, Jong-Won, TaekJoon Yi, Joo-Hyeok Kw, Jooeon Ahn, and Bokki Kim. "Arbitrary Sample Rate Conversion Architecture for High Output Sample Rate." Journal of Korean Institute of Communications and Information Sciences 44, no. 7 (July 31, 2019): 1248–56. http://dx.doi.org/10.7840/kics.2019.44.7.1248.

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Rittinghaus, Tim, and Birgit Glasmacher. "Is freezer cooling rate equal to sample cooling rate?" Cryobiology 85 (December 2018): 135. http://dx.doi.org/10.1016/j.cryobiol.2018.10.070.

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Hentschel, T., and G. Fettweis. "Sample rate conversion for software radio." IEEE Communications Magazine 38, no. 8 (2000): 142–50. http://dx.doi.org/10.1109/35.860866.

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Yao, Lin Xin, and Gan Yao. "High sample rate Doppler ultrasound system." Journal of the Acoustical Society of America 113, no. 1 (2003): 18. http://dx.doi.org/10.1121/1.1554183.

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Putzeys, Bruno J. G. "Sample rate converter using polynomial interpolation." Journal of the Acoustical Society of America 113, no. 5 (2003): 2394. http://dx.doi.org/10.1121/1.1584178.

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Kim, Jae-Hun, and Young-Sik Kim. "25MHz Sample Rate 8bit Thermometer DAC Design." Journal of the Institute of Electronics and Information Engineers 55, no. 3 (March 31, 2018): 29–33. http://dx.doi.org/10.5573/ieie.2018.55.3.29.

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Birru, D. "Optimized reduced sample rate sigma-delta modulation." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 44, no. 11 (1997): 896–906. http://dx.doi.org/10.1109/82.644043.

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Logsdon, S. D. "WITHIN SAMPLE VARIATION OF OXYGEN DIFFUSION RATE." Soil Science 168, no. 8 (August 2003): 531–39. http://dx.doi.org/10.1097/01.ss.0000085052.25696.c0.

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McFee, Brian. "resampy: efficient sample rate conversion in Python." Journal of Open Source Software 1, no. 8 (December 5, 2016): 125. http://dx.doi.org/10.21105/joss.00125.

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Dissertations / Theses on the topic "Sample rate"

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Rothacher, Fritz Markus. "Sample-rate conversion : algorithms and VLSI implementation /." [Konstanz] : Hartung-Gorre, 1995. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=10980.

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Walke, Richard Lewis. "High sample-rate Givens rotations for recursive least squares." Thesis, University of Warwick, 1997. http://wrap.warwick.ac.uk/36283/.

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The design of an application-specific integrated circuit of a parallel array processor is considered for recursive least squares by QR decomposition using Givens rotations, applicable in adaptive filtering and beamforming applications. Emphasis is on high sample-rate operation, which, for this recursive algorithm, means that the time to perform arithmetic operations is critical. The algorithm, architecture and arithmetic are considered in a single integrated design procedure to achieve optimum results. A realisation approach using standard arithmetic operators, add, multiply and divide is adopted. The design of high-throughput operators with low delay is addressed for fixed- and floating-point number formats, and the application of redundant arithmetic considered. New redundant multiplier architectures are presented enabling reductions in area of up to 25%, whilst maintaining low delay. A technique is presented enabling the use of a conventional tree multiplier in recursive applications, allowing savings in area and delay. Two new divider architectures are presented showing benefits compared with the radix-2 modified SRT algorithm. Givens rotation algorithms are examined to determine their suitability for VLSI implementation. A novel algorithm, based on the Squared Givens Rotation (SGR) algorithm, is developed enabling the sample-rate to be increased by a factor of approximately 6 and offering area reductions up to a factor of 2 over previous approaches. An estimated sample-rate of 136 MHz could be achieved using a standard cell approach and O.35pm CMOS technology. The enhanced SGR algorithm has been compared with a CORDIC approach and shown to benefit by a factor of 3 in area and over 11 in sample-rate. When compared with a recent implementation on a parallel array of general purpose (GP) DSP chips, it is estimated that a single application specific chip could offer up to 1,500 times the computation obtained from a single OP DSP chip.
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Liu, Kit-ying Ida. "Empirical exchange rate models : out-of-sample forecasts for the HK$/Yen exchange rate /." Hong Kong : University of Hong Kong, 1997. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20666895.

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Lee, Jeffrey C. "Design Considerations for a Variable sample Rate Signal Conditioning Module." International Foundation for Telemetering, 2008. http://hdl.handle.net/10150/606212.

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ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, California
Modern telemetry systems require flexible sampling rates for analog signal conditioning within telemetry encoders in order to optimize mission formats for varying data acquisition needs and data rate constraints. Implementing a variable sample rate signal conditioning module for a telemetry encoder requires consideration of several possible architectural topologies that place different system requirements on data acquisition modules within the encoder in order to maintain adequate signal fidelity of sensor information. This paper focuses on the requirements, design considerations and tradeoffs associated with differing architectural topologies for implementing a variable sample rate signal conditioning module and the resulting implications on the encoder system's data acquisition units.
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De, Boyrie Maria Eugenia. "Out-of-sample exchange rate forecasting structural and non-structural nonlinear approaches." FIU Digital Commons, 1994. http://digitalcommons.fiu.edu/etd/2727.

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Forecasting foreign exchange rates is a perennial dilemma for exporters, importers, foreign exchange rate traders, and the business community as a whole. Foreign exchange rate models using popular linear and non-linear specifications do not produce particularly accurate forecasts. In point of fact, these models have not improved much upon the random walk model, especially in out-of-sample forecasting. Given these results, this dissertation constructs and evaluates new forecasting models to generate as accurate as possible out-of-sample forecasts of foreign exchange rates. The information content of futures contracts on foreign exchange rates is investigated and used to forecast future exchange rates using alternative techniques, both structural (econometric) and non-structural (fuzzy) models. The results of two specifications of a structural model are compared against the well-known random walk model. The first specification assumes future exchange rates are determined by futures prices and a lagged structure of spot rates. The second specification assumes that future spot rates are a function of only a lagged structure of the futures prices. The forecasting accuracy of the models is tested for both in-sample and out-of-sample periods; out-of-sample tests range from the short term to the long term (30- to 180-day forecasts). The results indicate that the random walk model remains a competitive alternative. In out-of-sample predictions, however, we can improve upon it in certain cases. The results also show that the predictive accuracy of the models is better in the short term (30 to 60 days) than in the longer term (180 days).
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Guo, Ruijuan. "Sample comparisons using microarrays -- application of false discovery rate and quadratic logistic regression." Worcester, Mass. : Worcester Polytechnic Institute, 2007. http://www.wpi.edu/Pubs/ETD/Available/etd-010808-173747/.

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Guo, Ruijuan. "Sample comparisons using microarrays: - Application of False Discovery Rate and quadratic logistic regression." Digital WPI, 2008. https://digitalcommons.wpi.edu/etd-theses/28.

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In microarray analysis, people are interested in those features that have different characters in diseased samples compared to normal samples. The usual p-value method of selecting significant genes either gives too many false positives or cannot detect all the significant features. The False Discovery Rate (FDR) method controls false positives and at the same time selects significant features. We introduced Benjamini's method and Storey's method to control FDR, applied the two methods to human Meningioma data. We found that Benjamini's method is more conservative and that, after the number of the tests exceeds a threshold, increase in number of tests will lead to decrease in number of significant genes. In the second chapter, we investigate ways to search interesting gene expressions that cannot be detected by linear models as t-test or ANOVA. We propose a novel approach to use quadratic logistic regression to detect genes in Meningioma data that have non-linear relationship within phenotypes. By using quadratic logistic regression, we can find genes whose expression correlates to their phenotypes both linearly and quadratically. Whether these genes have clinical significant is a very interesting question, since these genes most likely be neglected by traditional linear approach.
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Peng, Song. "RESTORE PCM TELEMETRY SIGNAL WAVEFORM BY MAKING USE OF MULTI-SAMPLE RATE INTERPOLATION TECHNOLOGY." International Foundation for Telemetering, 1999. http://hdl.handle.net/10150/607318.

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International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada
There are two misty understandings about PCM telemetry system in conventional concept: Waveform can not be restored accurately; to be restored accurately, a measured signal must be sampled at a higher sample rate. This paper discusses that by making use of multi-sample rate DSP technology, the sample rate of a measured signal can be reduced in transmission equipment, or system precision can be retained even if the performance of low pass filter declined.
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Ghanavati, Goodarz. "Statistical Analysis of High Sample Rate Time-series Data for Power System Stability Assessment." ScholarWorks @ UVM, 2015. http://scholarworks.uvm.edu/graddis/333.

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The motivation for this research is to leverage the increasing deployment of the phasor measurement unit (PMU) technology by electric utilities in order to improve situational awareness in power systems. PMUs provide unprecedentedly fast and synchronized voltage and current measurements across the system. Analyzing the big data provided by PMUs may prove helpful in reducing the risk of blackouts, such as the Northeast blackout in August 2003, which have resulted in huge costs in past decades. In order to provide deeper insight into early warning signs (EWS) of catastrophic events in power systems, this dissertation studies changes in statistical properties of high-resolution measurements as a power system approaches a critical transition. The EWS under study are increases in variance and autocorrelation of state variables, which are generic signs of a phenomenon known as critical slowing down (CSD). Critical slowing down is the result of slower recovery of a dynamical system from perturbations when the system approaches a critical transition. CSD has been observed in many stochastic nonlinear dynamical systems such as ecosystem, human body and power system. Although CSD signs can be useful as indicators of proximity to critical transitions, their characteristics vary for different systems and different variables within a system. The dissertation provides evidence for the occurrence of CSD in power systems using a comprehensive analytical and numerical study of this phenomenon in several power system test cases. Together, the results show that it is possible extract information regarding not only the proximity of a power system to critical transitions but also the location of the stress in the system from autocorrelation and variance of measurements. Also, a semi-analytical method for fast computation of expected variance and autocorrelation of state variables in large power systems is presented, which allows one to quickly identify locations and variables that are reliable indicators of proximity to instability.
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Brownlow, Briana Nicole. "Patterns of Heart Rate Variability Predictive of Internalizing Symptoms in a Non-Clinical Youth Sample." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1518179804584445.

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Books on the topic "Sample rate"

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Large sample Hawaii birth abnormality rate determination. Honolulu, Hawaii: Research and Statistics Office, Hawaii State Dept. of Health, 1988.

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Rothacher, Fritz. Sample-rate conversion: Algorithms and VLSI implementation. Kothacher: Hartung-Gorre Verlag, 1995.

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The silent minority: Nonrespondents on sample surveys. Cambridge, UK: Polity Press, 1987.

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The silent minority: Nonrespondents on sample surveys. Boulder, Colo: Westview Press, 1987.

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Walke, Richard Lewis. High sample-rate Givens rotations for recursive least squares. [s.l.]: typescript, 1997.

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Moura, Eduardo C. How to determine sample size and estimate failure rate in life testing. Milwaukee, Wis: ASQC Quality Press, 1991.

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The hunt for the last respondent: Nonresponse in sample surveys. The Hague: SCP, Social and Cultural Planning Office of the Netherlands, 2005.

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Kuo, Biing-Shen. The behaviour of the real exchange rate: A re-examination using finite sample approach. London: Centre for Economic Policy Research, 1997.

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Lieth, Helmut. Correlation analyses between weatherclasses and blood sedimentation rate fluctuations of a population sample in Leiden, The Netherlands. Amsterdam, The Netherlands: SPB Academic Pub., 1996.

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Park, Jae Won. The information in the term structure of interest rates: Out-of-sample forecasting performance. Fontainebleau: INSEAD, 1990.

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Book chapters on the topic "Sample rate"

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Pirkle, Will C. "Sample Rate Conversion." In Designing Audio Effect Plugins in C++, 624–43. Second edition. | New York, NY : Routledge, 2019.: Routledge, 2019. http://dx.doi.org/10.4324/9780429490248-22.

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Chow, Shein-Chung, Jun Shao, Hansheng Wang, and Yuliya Lokhnygina. "Sample Size for Clinical Trials with Extremely Low Incidence Rate." In Sample Size Calculations in Clinical Research: Third Edition, 373–88. Third edition. | Boca Raton : Taylor & Francis, 2017. | Series: Chapman & Hall/CRC biostatistics series | “A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc.”: Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315183084-17.

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Pliquett, Uwe. "Electrical Characterization in Time Domain – Sample Rate and ADC Precision." In IFMBE Proceedings, 854–57. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11128-5_212.

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Xu, Yunpeng, Changshui Zhang, and Naijiang Lu. "A Bayesian Method for High-Frequency Restoration of Low Sample-Rate Speech." In Pattern Recognition and Data Mining, 544–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11551188_60.

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Martins, João Paulo, Rui Santos, and Miguel Felgueiras. "A Maximum Likelihood Estimator for the Prevalence Rate Using Pooled Sample Tests." In Springer Proceedings in Mathematics & Statistics, 99–110. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18029-8_8.

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Chow, Shein-Chung, Yuanyuan Kong, and Shih-Ting Chiu. "Sample Size for HIV-1 Vaccine Clinical Trials with Extremely Low Incidence Rate." In Quantitative Methods for HIV/AIDS Research, 17–40. Boca Raton : Taylor & Francis, 2017. | “A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc.”: Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315120805-3.

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Finn, David W. "Response Rate Stimulants in Mail Surveys: A Potential Source of Sample Composition Bias." In Proceedings of the 1982 Academy of Marketing Science (AMS) Annual Conference, 549. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16946-0_141.

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D’Arco, M., E. Napoli, and E. Zacharelos. "Digital Circuit for the Arbitrary Selection of Sample Rate in Digital Storage Oscilloscopes." In Lecture Notes in Electrical Engineering, 183–89. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37277-4_21.

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Kieser, Meinhard. "A General Approach for Controlling the Type I Error Rate for Blinded Sample Size Recalculation." In Springer Series in Pharmaceutical Statistics, 207. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49528-2_19.

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Girardi, L., and E. Bica. "A Comparison Between a Color Evolution Model and New Sample of LMC Clusters: Formation Rate." In The Stellar Populations of Galaxies, 423. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2434-8_90.

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Conference papers on the topic "Sample rate"

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Park, Sangil. "Digital Sample-Rate Converters." In International Congress & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1991. http://dx.doi.org/10.4271/910788.

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Baltic, Milan, Aleksandar Rakic, and Milan Ponjavic. "Variable sample rate acquisiton platform." In 2013 21st Telecommunications Forum Telfor (TELFOR). IEEE, 2013. http://dx.doi.org/10.1109/telfor.2013.6716262.

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Zeineddine, A., S. Paquelet, M. Kanj, C. Moy, A. Nafkha, and P. Y. Jezequel. "RECONFIGURABLE NEWTON STRUCTURE FOR SAMPLE RATE CONVERSION." In 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2018. http://dx.doi.org/10.1109/globalsip.2018.8646354.

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Melgaard, Jacob, Claus Graff, Peter Sorensen, Kasper Sorensen, Samuel Emil Schmidt, and Johannes Struijk. "Effect of Sample Rate on saECG Spectrum." In 2016 Computing in Cardiology Conference. Computing in Cardiology, 2016. http://dx.doi.org/10.22489/cinc.2016.306-499.

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Manning, C., and S. Green. "256. Sampling Rate and Sample Capacity Studies in Optimizing Diffusive Samplers Designs." In AIHce 2006. AIHA, 2006. http://dx.doi.org/10.3320/1.2753411.

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Dolecek, Gordana Jovanovic. "Modified CIC filter for rational sample rate conversion." In 2007 International Symposium on Communications and Information Technologies. IEEE, 2007. http://dx.doi.org/10.1109/iscit.2007.4392024.

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Jovanovic Dolecek, G., and F. J. Trejo Torres. "Multiplierless multiband filter for fractional sample rate conversion." In 2008 Mosharaka International Conference on Communications, Propagation and Electronics (MIC-CPE '08). IEEE, 2008. http://dx.doi.org/10.1109/miccpe.2008.4555746.

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Wang, Tianqi, and Cheng Li. "Sample Rate Conversion Technology in Software Defined Radio." In 2006 Canadian Conference on Electrical and Computer Engineering. IEEE, 2006. http://dx.doi.org/10.1109/ccece.2006.277567.

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Hillard, G., and D. Ferguson. "Measured rate of arcing from an anodized aluminum sample on the SAMPIE flight experiment." In 33rd Aerospace Sciences Meeting and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1995. http://dx.doi.org/10.2514/6.1995-487.

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Chen, Feng, Jing Dai, Bingsheng Wang, Sambit Sahu, Milind Naphade, and Chang-Tien Lu. "Activity analysis based on low sample rate smart meters." In the 17th ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2020408.2020450.

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Reports on the topic "Sample rate"

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Sullivan, B., V. Coccia, A. Dentamaro, J. Roadcap, D. Mizuno, and T. Kuchar. High Sample Rate Sensor Imaging Technique. Fort Belvoir, VA: Defense Technical Information Center, March 2005. http://dx.doi.org/10.21236/ada438381.

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Libert, John M., Shahram Orandi, John D. Grantham, and Michael D. Garris. A Spectral Analytic Method for Fingerprint Image Sample Rate Estimation. National Institute of Standards and Technology, February 2014. http://dx.doi.org/10.6028/nist.ir.7968.

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Clarida, Richard, Lucio Sarno, Mark Taylor, and Giorgio Valente. The Out-of-Sample Success of Term Structure Models as Exchange Rate Predictors: A Step Beyond. Cambridge, MA: National Bureau of Economic Research, November 2001. http://dx.doi.org/10.3386/w8601.

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Almond, P. M., D. I. Kaplan, C. A. Langton, D. B. Stefanko, W. A. Spencer, A. Hatfield, and Y. Arai. Method Evaluation And Field Sample Measurements For The Rate Of Movement Of The Oxidation Front In Saltstone. Office of Scientific and Technical Information (OSTI), August 2012. http://dx.doi.org/10.2172/1056464.

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Harter, Rachel M., Joseph P. McMichael, Derick S. Brown, Ashley Amaya, Trent D. Buskirk, and David Malarek. Telephone Appends for Address-Based Samples— An Introduction. RTI Press, February 2018. http://dx.doi.org/10.3768/rtipress.2018.op.0050.1802.

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Surveys with samples selected from an address frame derived from US Postal Service sources are often referred to as address-based sampling (ABS) surveys. For an ABS survey that is primarily conducted by mail, web, or face-to-face, sometimes it is helpful to have a telephone number corresponding to the sample addresses for setting appointments or conducting nonresponse follow-up prompts. The usefulness of a telephone contact mode in a mixed mode ABS design depends on both the percentage of addresses for which telephone numbers can be appended (append rate or match rate) and the accuracy of the telephone numbers associated with addresses. Before planning a telephone contact as part of a mixed-mode study, the designer should know the likely effectiveness of the approach. This paper focuses primarily on append rate information, with a discussion of accuracy rates. For a single ABS frame, telephone match rates vary by geography, address type, match vendor, and by landline vs. cell telephone number. Using very large samples of addresses from a total US ABS frame, we estimated state and national telephone append rates from Marketing Systems Group's sources. The append rates are summarized here and interactively at the website http://abs.rti.org/atlas/.
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Robbins, Frederick W., and Theresa Keys. The Burning Rate Behavior of Pure Nitrocellulose Propellant Samples. Fort Belvoir, VA: Defense Technical Information Center, March 1993. http://dx.doi.org/10.21236/ada261009.

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McNichols, D. T., and W. J. Padgett. Nonparametric Methods for Hazard Rate Estimation from Right-Censored Samples. Fort Belvoir, VA: Defense Technical Information Center, August 1985. http://dx.doi.org/10.21236/ada159131.

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Shieh, Leang-San, and Guanrong Chen. Robust Optimal Digital Control of Uncertain Multi-Rate Sampled-Data Systems. Fort Belvoir, VA: Defense Technical Information Center, January 1998. http://dx.doi.org/10.21236/ada344559.

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Martino, Chris, John Pareizs, and Wesley Woodham. INVESTIGATION OF THERMOLYTIC HYDROGEN GENERATION RATE IN TANK 44 DISSOLVED SALTCAKE SAMPLES. Office of Scientific and Technical Information (OSTI), February 2020. http://dx.doi.org/10.2172/1602975.

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Padgett, W. J. Nonparametric Estimation of Density and Hazard Rate Functions when Samples are Censored. Fort Belvoir, VA: Defense Technical Information Center, January 1985. http://dx.doi.org/10.21236/ada150946.

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