Relevant bibliographies by topics / Frequency sampling

Contents

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

Academic literature on the topic 'Frequency sampling'

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

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Journal articles on the topic "Frequency sampling"

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Zhou, Yuewen, Fangzheng Zhang, and Shilong Pan. "Instantaneous frequency analysis of broadband LFM signals by photonics-assisted equivalent frequency sampling." Chinese Optics Letters 19, no. 1 (2021): 013901. http://dx.doi.org/10.3788/col202119.013901.

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Brown, T. W., M. Hakkarainen, and T. S. Fiez. "Frequency-Dependent Sampling Linearity." IEEE Transactions on Circuits and Systems I: Regular Papers 56, no. 4 (2009): 740–53. http://dx.doi.org/10.1109/tcsi.2008.2003378.

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Chambers, Marcus J. "Cointegration and sampling frequency." Econometrics Journal 14, no. 2 (2011): 156–85. http://dx.doi.org/10.1111/j.1368-423x.2010.00329.x.

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Coulson, A. J., R. G. Vaughan, and M. A. Poletti. "Frequency-shifting using bandpass sampling." IEEE Transactions on Signal Processing 42, no. 6 (1994): 1556–59. http://dx.doi.org/10.1109/78.286975.

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Kukrer, O., and H. Komurcugil. "Variable sampling frequency PWM waveforms." IEEE Power Electronics Letters 1, no. 1 (2003): 14–16. http://dx.doi.org/10.1109/lpel.2003.816000.

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Robinson, Enders, and Dean Clark. "Sampling and the Nyquist frequency." Leading Edge 10, no. 3 (1991): 51–53. http://dx.doi.org/10.1190/1.1436812.

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Song, Jue, Songnian Fu, Bin Liu, Ming Tang, Perry Shum, and Deming Liu. "Impact of Sampling Source Repetition Frequency in Linear Optical Sampling." IEEE Photonics Technology Letters 28, no. 1 (2016): 15–18. http://dx.doi.org/10.1109/lpt.2015.2478877.

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Perron, Pierre. "Test Consistency with Varying Sampling Frequency." Econometric Theory 7, no. 3 (1991): 341–68. http://dx.doi.org/10.1017/s0266466600004503.

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This paper considers the consistency property of some test statistics based on a time series of data. While the usual consistency criterion is based on keeping the sampling interval fixed, we let the sampling interval take any equispaced path as the sample size increases to infinity. We consider tests of the null hypotheses of the random walk and randomness against positive autocorrelation (stationary or explosive). We show that tests of the unit root hypothesis based on the first-order correlation coefficient of the original data are consistent as long as the span of the data is increasing. Tests of the same hypothesis based on the first-order correlation coefficient of the first-differenced data are consistent against stationary alternatives only if the span is increasing at a rate greater than T½, where T is the sample size. On the other hand, tests of the randomness hypothesis based on the first-order correlation coefficient applied to the original data are consistent as long as the span is not increasing too fast. We provide Monte Carlo evidence on the power, in finite samples, of the tests Studied allowing various combinations of span and sampling frequencies. It is found that the consistency properties summarize well the behavior of the power in finite samples. The power of tests for a unit root is more influenced by the span than the number of observations while tests of randomness are more powerful when a small sampling frequency is available.
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Whysong, G. L., and W. W. Brady. "Frequency Sampling and Type II Errors." Journal of Range Management 40, no. 5 (1987): 472. http://dx.doi.org/10.2307/3899614.

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Nates, Joseph L., Egbert Pravinkumar, Kristen Price, et al. "ENVIRONMENTAL SAMPLING DURING HIGH FREQUENCY VENTILATION." Critical Care Medicine 34 (December 2006): A88. http://dx.doi.org/10.1097/00003246-200612002-00303.

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Dissertations / Theses on the topic "Frequency sampling"

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bi, xiaofei. "Compressed Sampling for High Frequency Receivers Applications." Thesis, Högskolan i Gävle, Avdelningen för elektronik, matematik och naturvetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-10877.

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In digital signal processing field, for recovering the signal without distortion, Shannon sampling theory must be fulfilled in the traditional signal sampling. However, in some practical applications, it is becoming an obstacle because of the dramatic increase of the costs due to increased volume of the storage and transmission as a function of frequency for sampling. Therefore, how to reduce the number of the sampling in analog to digital conversion (ADC) for wideband and how to compress the large data effectively has been becoming major subject for study. Recently, a novel technique, so-called “compressed sampling”, abbreviated as CS, has been proposed to solve the problem. This method will capture and represent compressible signals at a sampling rate significantly lower than the Nyquist rate.   This paper not only surveys the theory of compressed sampling, but also simulates the CS with the software Matlab. The error between the recovered signal and original signal for simulation is around -200dB. The attempts were made to apply CS. The error between the recovered signal and original one for experiment is around -40 dB which means the CS is realized in a certain extent. Furthermore, some related applications and the suggestions of the further work are discussed.
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Myslicki, Stefan Leopold 1953. "A VARIABLE SAMPLING FREQUENCY CUMULATIVE SUM CONTROL CHART SCHEME." Thesis, The University of Arizona, 1987. http://hdl.handle.net/10150/276503.

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This study uses Monte Carlo simulation to examine the performance of a variable frequency sampling cumulative sum control chart scheme for controlling the mean of a normal process. The study compares the performance of the method with that of a standard fixed interval sampling cumulative sum control chart scheme. The results indicate that the variable frequency sampling cumulative sum control chart scheme is superior to the standard cumulative sum control chart scheme in detecting a small to moderate shift in the process mean.
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Lin, Chun-Ching. "Demodulation of Narrowband Radio Frequency Signals by Aliasing Sampling." PDXScholar, 1996. https://pdxscholar.library.pdx.edu/open_access_etds/5286.

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The objective of this thesis is to study the demodulation of narrowband radio frequency signals by aliasing sampling in order to reduce the sampling rate. The spectrum can be recreated at the lower frequency position by aliasing sampling. However, if the sampling rate is deviated from the desired one, error will occur. The sensitivity to the frequency error of aliasing sampling is studied. One main reason of the deviation of the sampling rate is the frequency drifting of the local oscillator. Being able to compensate the oscillator drifting errors inexpensively, automatic frequency control (AFC) loops are important at receivers. Two major digital AFC algorithms are studied. One is the Phase method AFC, and the other is the Magnitude method AFC. Study indicates that both methods perform almost equally well. One adaptive AFC algorithm is also proposed. The scheme of the adaptive AFC algorithm is to use Upper-bound and Lower-bound techniques to squeeze the frequency errors. It is shown that the adaptive AFC algorithm can achieve up to 20 dB average signal-to-noise power ratio over the Magnitude method AFC under a noisy environment.
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Milley, Andrew J. "Computer-Aided Design and Frequency Domain Analysis of Sampling Circuits." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1242665614.

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Karvonen, S. (Sami). "Charge-domain sampling of high-frequency signals with embedded filtering." Doctoral thesis, University of Oulu, 2006. http://urn.fi/urn:isbn:9514279875.

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Abstract Subsampling can be used in a radio receiver to perform signal downconversion and sample-and-hold operations in order to relieve the operation frequency and bandwidth requirements of the subsequent discrete-time circuitry. However, due to the inherent aliasing behaviour of wideband noise and interference in subsampling, and the difficulty of implementing appropriate bandpass anti-aliasing filtering at high frequencies, straightforward use of a low subsampling rate can result in significant degradation of the receiver dynamic range. The aim of this thesis is to investigate and implement methods for integrating filtering into high-frequency signal sampling and downconversion by subsampling to alleviate the requirements for additional front-end filters and to mitigate the effects of noise and out-of-band signal aliasing, thereby facilitating use in integrated high-quality radio receivers. The charge-domain sampling technique studied here allows simple integration of both continuous-and discrete-time filtering functions into high-frequency signal sampling. Gated current integration results in a lowpass sin(x)/x(sinc(x)) response capable of performing built-in anti-aliasing filtering in baseband signal sampling. Weighted integration of several successive current samples can be further used to obtain an embedded discrete-time finite-impulse-response (FIR) filtering response, which can be used for internal anti-aliasing and image-rejection filtering in the downconversion of bandpass signals by subsampling. The detailed analysis of elementary charge-domain sampling circuits presented here shows that the use of integrated FIR filtering with subsampling allows acceptable noise figures to be achieved and can provide effective internal anti-aliasing rejection. The new methods for increasing the selectivity of elementary charge-domain sampling circuits presented here enable the integration of advanced, digitally programmable FIR filtering functions into high-frequency signal sampling, thereby markedly relieving the requirements for additional anti-aliasing, image rejection and possibly even channel selection filters in a radio receiver. BiCMOS and CMOS IF sampler implementations are presented in order to demonstrate the feasibility of the charge-domain sampling technique for integrated anti-aliasing and image-rejection filtering in IF signal quadrature downconversion by subsampling. Circuit measurements show that this sampling technique for built-in filtering results in an accurate frequency response and allows the use of high subsampling ratios while still achieving a competitive dynamic range.
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Ninov, Valentin. "Two-dimensional zero-phase FIR filter design with nonuniform frequency sampling." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0002/MQ43655.pdf.

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Eng, Frida. "Non-Uniform Sampling in Statistical Signal Processing." Doctoral thesis, Linköping : Department of Electrical Engineering, Linköpings universitet, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8480.

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Datta, Srabosti. "POWER REDUCTION BY DYNAMICALLY VARYING SAMPLING RATE." UKnowledge, 2006. http://uknowledge.uky.edu/gradschool_theses/275.

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In modern digital audio applications, a continuous audio signal stream is sampled at a fixed sampling rate, which is always greater than twice the highest frequency of the input signal, to prevent aliasing. A more energy efficient approach is to dynamically change the sampling rate based on the input signal. In the dynamic sampling rate technique, fewer samples are processed when there is little frequency content in the samples. The perceived quality of the signal is unchanged in this technique. Processing fewer samples involves less computation work; therefore processor speed and voltage can be reduced. This reduction in processor speed and voltage has been shown to reduce power consumption by up to 40% less than if the audio stream had been run at a fixed sampling rate.
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Nader, Charles. "Signal Shaping and Sampling-based Measurement Techniques for Improved Radio Frequency Systems." Doctoral thesis, KTH, Signalbehandling, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-95404.

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Wireless communication systems are omnipresent in our day-to-day life, with high expectations regarding capacity, reliability and power efficiency. In order to satisfy the capacity and reliability expectations, today's wireless systems are adopting sophisticated modulation schemes, such as orthogonal frequency division multiplexing (OFDM), which shape today's wireless signals with large bandwidths and high crest factors. On top of that, it is anticipated that different wireless systems/standards will co-exist and share the same radio frequency (RF) front-end in order to reduce the network implementation cost.   Such signals characteristics and systems coexistence put high requirements on the amplification stage which in best scenarios is considered weakly nonlinear. As a result, the power amplifier needs to be backed-off for linear operation. However, such power back-off reduces the operation's efficiency. Reducing the crest factor of the wireless signal and the possibility to linearize by means of digital pre-distortion the operation behavior of the power amplifier when operated near its maximum allowed continuous wave (CW) operating power range would lead to the optimal linearity and efficiency of operation.   In order to achieve a good linearization performance, accurate baseband behavioral models are needed which requires measuring time domain signals whose spectra spread largely due to the nonlinear operation of the power amplifier. Such spectrum spreading, denoted by spectral regrowth, puts high requirements on today's sampling-based measurement systems as a trade-of between the sampling rate and amplitude resolution exists in today's generation of analog-to-digital converters, in addition to a limitation in the available analog bandwidth. Overcoming such measurement challenges could lead to the design of expensive measurement systems which is not favorable.   In this thesis, the performance of RF transmitters is improved by combining the use of a smart crest factor reduction technique with an enhanced digital pre-distortion technique which allows operating the power amplifier near its CW 1-dB compression point, offering a significant increase in the efficiency of operation while satisfying the standard constraints on information error and spectral emission. Furthermore, the performance of RF measurement receivers is improved by reducing the requirements on the digital bandwidth by means of an evolved harmonic sampling technique, and by reducing the requirements on the analog bandwidth and design cost by means of a digital bandwidth interleaving technique and a signal separation technique based on an advanced sparse reconstruction methodology.<br>Trådlösa kommunikationssystem förekommer överallt i vår vardag, med höga förväntningar på kapacitet, tillförlitlighet och energieffektivitet. För att uppfylla förväntningar på kapacitet och tillförlitlighet är dagens trådlösa system utrustade med avancerade modulationsmetoder, såsom Orthogonal Frequency Division Multiplexing (OFDM), vilket medför att dagens trådlösa signaler har stora bandbredder och höga toppfaktorer. Därutöver planeras det för att olika trådlösa system/standarder kommer att samexistera och samutnyttja komponenter i gränssnittet mot radiosignaler, s.k. RF front-end, för att därigenom minska kostnader för nätverk. Egenskaperna hos dessa signaler och samexisterande system ställer höga krav på förstärkarsteg som i bästa fall kan anses svagt olinjära. Som ett resultat av detta behöver effektförstärkaren arbetspunkt flyttas för förstärkaren skall arbeta i det linjära området, men en sådan förflyttning minskar systemets verkningsgrad. Genom att reducera toppfaktorn på den trådlösa signalen samt att linjärisera förstärkarsteget genom digital förförvrängning, även kallad predistortion, hos effektförstärkaren när den drivs nära sin högsta tillåtna arbetspunkt för en kontinuerlig signal (CW) kan optimal linjäritet och effektiv drift erhållas. För att uppnå god linjäriseringsprestanda krävs noggranna modeller som beskriver beteende i basbandet. Att ta fram dessa modeller kräver tidsdomänmätningar av signaler vars spektra är bredbandiga, till stor del beroende på icke-linjär drift av effektförstärkaren. Bredbandiga spektra ställer höga krav på dagens samplande mätsystem i och med kompromissen mellan samplingsfrekvens och upplösning i amplitud finns i dagens generation av analog till digital omvandlare; dessutom finns en begränsning i tillgänglig analog bandbredd. Att lösa dessa utmanande mätproblem kan leda till utformning av dyra mätsystem vilket inte är önskvärt. I denna avhandling förbättras prestandan hos en radiosändare genom en kombination av smart toppfaktorreduktion och förbättrad digital predistortionsteknik som gör det möjligt att driva effektförstärkaren nära sin 1 dB kompressionspunkt, vilket erbjuder en betydande ökning av systemets verkningsgrad samtidigt som det uppfyller standarders krav avseende vektornoggrannhet och spektral spridning. Dessutom har prestandan på mätutrustningen för radiofrekvenser (RF) förbättras genom att minska kraven på digital bandbredd med hjälp av en nyutvecklad harmonisk samplingsteknik, och genom att minska kraven på den analoga bandbredden och konstruktionskostnad med hjälp av en teknik att intersekvensera signaler i den digitala frekvensdomänen samt med en signalseparationsteknik baserad på en avancerad rekonstruktionsmetod för glesa signaler.<br>QC 20120605
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Kumar, Rajendra. "Differential Sampling for Fast Frequency Acquisition Via Adaptive Extended Least Squares Algorithm." International Foundation for Telemetering, 1987. http://hdl.handle.net/10150/615321.

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International Telemetering Conference Proceedings / October 26-29, 1987 / Town and Country Hotel, San Diego, California<br>This paper presents a differential signal model along with appropriate sampling techniques for least squares estimation of the frequency and frequency derivatives and possibly the phase and amplitude of a sinusoid received in the presence of noise. The proposed algorithm is recursive in measurements and thus the computational requirement increases only linearly with the number of measurements. The dimension of the state vector in the proposed algorithm does not depend upon the number of measurements and is quite small, typically around four. This is an advantage when compared to previous algorithms wherein the dimension of the state vector increases monotonically with the product of the frequency uncertainty and the observation period. Such a computational simplification may possibly result in some loss of optimality. However, by applying the sampling techniques of the paper such a possible loss in optimality can be made small.
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Books on the topic "Frequency sampling"

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Sound synthesis and sampling. Focal Press, 1996.

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Sound synthesis and sampling. 2nd ed. Focal Press, 2004.

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Schuring, J. Frequency response analysis of hybrid systems. National Aerospace Laboratory, 1987.

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Hogan, Jeffrey A. Time-frequency and time-scale methods: Adaptive decompositions, uncertainty principles, and sampling. Birkhauser, 2004.

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Soltani, Faouzi. FIR filter design by nonuniform sampling in the time and frequency domain. University of Birmingham, 1989.

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1963-, Lakey Joseph D., ed. Time-frequency and time-scale methods: Adaptive decompositions, uncertainty principles, and sampling. Birkhauser, 2005.

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Mason, Richard R. Sampling Western Spruce Budworm larvae by frequency of occurrence on lower crown branches. U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 1990.

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Mason, Richard R. Sampling Western Spruce Budworm larvae by frequency of occurrence on lower crown branches. U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 1990.

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Flannagan, J. F. Studies on some riverine insect emergence traps: Effects of sampling frequency and trap design. Central and Arctic Region, Dept. of Fisheries and Oceans, 1994.

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A, Sprague Lori. Effects of storm-sampling frequency on estimation of water-quality loads and trends in two tributaries to Chesapeake Bay in Virginia. U.S. Dept. of the Interior, U.S. Geological Survey, 2001.

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Book chapters on the topic "Frequency sampling"

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Weik, Martin H. "sampling frequency." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_16574.

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Funk, James E., and Dennis R. Dinger. "Sampling and Test Frequency." In Predictive Process Control of Crowded Particulate Suspensions. Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-3118-0_38.

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Madych, Wolodymyr R. "Sampling Series, Refinable Sampling Kernels, and Frequency Band Limited Functions." In Sampling: Theory and Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36291-1_4.

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Kaiser, Gerald. "Discrete Time-Frequency Analysis and Sampling." In A Friendly Guide to Wavelets. Birkhäuser Boston, 2010. http://dx.doi.org/10.1007/978-0-8176-8111-1_5.

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Herley, Cormac, and Ping Wah Wong. "Efficient Minimum Rate Sampling of Signals with Frequency Support over Non-Commensurable Sets." In Modern Sampling Theory. Birkhäuser Boston, 2001. http://dx.doi.org/10.1007/978-1-4612-0143-4_13.

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Bretthorst, G. Larry. "The Near-Irrelevance of Sampling Frequency Distributions." In Maximum Entropy and Bayesian Methods Garching, Germany 1998. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4710-1_3.

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Bi, Guoan, and Sanjit K. Mitra. "Sampling Rate Conversion in the Frequency Domain." In Streamlining Digital Signal Processing. John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118316948.ch45.

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Mugler, Dale H., and Stuart Clary. "Frequency Determination Using the Discrete Hermite Transform." In New Perspectives on Approximation and Sampling Theory. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08801-3_16.

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Pei, Zheng-guo. "The Sampling Theory of the Binary Random Field Decides the Relation about Point and Plane of the Extra Rainstorms." In Hydrologic Frequency Modeling. Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3953-0_24.

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Ladekar, Mahesh, Yashwant Joshi, and Ramchandra Manthalkar. "Nonuniform Frequency Sampling Approach to FIR Filter Design." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1513-8_74.

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Conference papers on the topic "Frequency sampling"

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Joshi, Chaitali, Alessandro Farsi, and Alexander Gaeta. "Frequency-Domain Boson Sampling." In CLEO: QELS_Fundamental Science. OSA, 2017. http://dx.doi.org/10.1364/cleo_qels.2017.ftu1f.1.

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Dey, Sourav R., and Alan V. Oppenheim. "Frequency-Shaped Randomized Sampling." In 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.367131.

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Holighaus, Nicki, Peter Balazs, and Christoph Wiesmeyr. "Time-frequency representations for nonlinear frequency scales — Coorbit spaces and discretization." In 2015 International Conference on Sampling Theory and Applications (SampTA). IEEE, 2015. http://dx.doi.org/10.1109/sampta.2015.7148865.

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Penzin, Maxim S., and Nikolay V. Ilyin. "Sampling of frequency-modulated signals." In 2014 XXXIth URSI General Assembly and Scientific Symposium (URSI GASS). IEEE, 2014. http://dx.doi.org/10.1109/ursigass.2014.6929273.

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Yasuda, N. "Asynchronous Sampling Frequency Converter IC." In IEEE International Conference on Consumer Electronics. IEEE, 1994. http://dx.doi.org/10.1109/icce.1994.582298.

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Fedyukovich, Grigory, Samuel J. Kaufman, and Rastislav Bodik. "Sampling invariants from frequency distributions." In 2017 Formal Methods in Computer-Aided Design (FMCAD). IEEE, 2017. http://dx.doi.org/10.23919/fmcad.2017.8102247.

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Diederichs, Benedikt, and Armin Iske. "Projection-based multivariate frequency estimation." In 2017 International Conference on Sampling Theory and Applications (SampTA). IEEE, 2017. http://dx.doi.org/10.1109/sampta.2017.8024446.

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Banda, Daliso, Osamu Wada, Tuan Thanh Ta, Suguru Kameda, Noriharu Suematsu, and Kazuo Tsubouchi. "Direct RF under sampling reception method with lower sampling frequency." In 2013 Asia Pacific Microwave Conference - (APMC 2013). IEEE, 2013. http://dx.doi.org/10.1109/apmc.2013.6694844.

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Xu Yang, Yilin Chang, Junyan Huo, and Bingbing Li. "Frequency based down-sampling/up-sampling algorithm for chrominance component." In 2010 International Conference On Computer and Communication Technologies in Agriculture Engineering (CCTAE). IEEE, 2010. http://dx.doi.org/10.1109/cctae.2010.5543412.

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Giommi, Paolo, Elisabetta Cavazzuti, Sara Cutini, Andrea Tramacere, and Silvia Raino'. "The multi-frequency behaviour of Blazars." In The Extreme sky: Sampling the Universe above 10 keV. Sissa Medialab, 2010. http://dx.doi.org/10.22323/1.096.0040.

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Reports on the topic "Frequency sampling"

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Lin, Chun-Ching. Demodulation of Narrowband Radio Frequency Signals by Aliasing Sampling. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.7159.

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Mason, R. R., and R. C. Beckwith. Sampling western spruce budworm larvae by frequency of occurrence on lower crown branches. U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1990. http://dx.doi.org/10.2737/pnw-rn-497.

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Stockman, Christine T., Halim A. Alsaed, Charles R. Bryan, Steven C. Marschman, and John M. Scaglione. Evaluation of the Frequency for Gas Sampling for the High Burnup Confirmatory Data Project. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1364086.

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Stockman, Christine T., Halim A. Alsaed, and Charles R. Bryan. Draft evaluation of the frequency for gas sampling for the high burnup confirmatory data project. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1235985.

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Griffin, Andrew, Sean Griffin, Kristofer Lasko, et al. Evaluation of automated feature extraction algorithms using high-resolution satellite imagery across a rural-urban gradient in two unique cities in developing countries. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40182.

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Feature extraction algorithms are routinely leveraged to extract building footprints and road networks into vector format. When used in conjunction with high resolution remotely sensed imagery, machine learning enables the automation of such feature extraction workflows. However, many of the feature extraction algorithms currently available have not been thoroughly evaluated in a scientific manner within complex terrain such as the cities of developing countries. This report details the performance of three automated feature extraction (AFE) datasets: Ecopia, Tier 1, and Tier 2, at extracting building footprints and roads from high resolution satellite imagery as compared to manual digitization of the same areas. To avoid environmental bias, this assessment was done in two different regions of the world: Maracay, Venezuela and Niamey, Niger. High, medium, and low urban density sites are compared between regions. We quantify the accuracy of the data and time needed to correct the three AFE datasets against hand digitized reference data across ninety tiles in each city, selected by stratified random sampling. Within each tile, the reference data was compared against the three AFE datasets, both before and after analyst editing, using the accuracy assessment metrics of Intersection over Union and F1 Score for buildings and roads, as well as Average Path Length Similarity (APLS) to measure road network connectivity. It was found that of the three AFE tested, the Ecopia data most frequently outperformed the other AFE in accuracy and reduced the time needed for editing.
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6

Leis, Sherry. Vegetation community monitoring at Lincoln Boyhood National Memorial: 2011–2019. National Park Service, 2021. http://dx.doi.org/10.36967/nrr-2284711.

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Lincoln Boyhood National Memorial celebrates the lives of the Lincoln family including the final resting place of Abraham’s mother, Nancy Hanks Lincoln. Lincoln’s childhood in Indiana was a formative time in the life our 16th president. When the Lincoln family arrived in Indiana, the property was covered in the oak-hickory forest type. They cleared land to create their homestead and farm. Later, designers of the memorial felt that it was important to restore woodlands to the site. The woodlands would help visitors visualize the challenges the Lincoln family faced in establishing and maintaining their homestead. Some stands of woodland may have remained, but significant restoration efforts included extensive tree planting. The Heartland Inventory and Monitoring Network began monitoring the woodland in 2011 with repeat visits every four years. These monitoring efforts provide a window into the composition and structure of the wood-lands. We measure both overstory trees and the ground flora within four permanently located plots. At these permanent plots, we record each species, foliar cover estimates of ground flora, diameter at breast height of midstory and overstory trees, and tree regeneration frequency (tree seedlings and saplings). The forest species composition was relatively consistent over the three monitoring events. Climatic conditions measured by the Palmer Drought Severity Index indicated mild to wet conditions over the monitoring record. Canopy closure continued to indicate a forest structure with a closed canopy. Large trees (&gt;45 cm DBH) comprised the greatest amount of tree basal area. Sugar maple was observed to have the greatest basal area and density of the 23 tree species observed. The oaks characteristic of the early woodlands were present, but less dominant. Although one hickory species was present, it was in very low abundance. Of the 17 tree species recorded in the regeneration layer, three species were most abundant through time: sugar maple (Acer saccharum), red bud (Cercis canadensis), and ash (Fraxinus sp.). Ash recruitment seemed to increase over prior years and maple saplings transitioned to larger size classes. Ground flora diversity was similar through time, but alpha and gamma diversity were slightly greater in 2019. Percent cover by plant guild varied through time with native woody plants and forbs having the greatest abundance. Nonnative plants were also an important part of the ground flora composition. Common periwinkle (Vinca minor) and Japanese honeysuckle (Lonicera japonica) continued to be the most abundant nonnative species, but these two species were less abundant in 2019 than 2011. Unvegetated ground cover was high (mean = 95%) and increased by 17% since 2011. Bare ground increased from less than 1% in 2011 to 9% in 2019, but other ground cover elements were similar to prior years. In 2019, we quantified observer error by double sampling two plots within three of the monitoring sites. We found total pseudoturnover to be about 29% (i.e., 29% of the species records differed between observers due to observer error). This 29% pseudoturnover rate was almost 50% greater than our goal of 20% pseudoturnover. The majority of the error was attributed to observers overlooking species. Plot frame relocation error likely contributed as well but we were unable to separate it from overlooking error with our design.
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7

Effects of storm-sampling frequency on estimation of water-quality loads and trends in two tributaries to Chesapeake Bay in Virginia. US Geological Survey, 2001. http://dx.doi.org/10.3133/wri014136.

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