Relevant bibliographies by topics / Discrete time

Academic literature on the topic 'Discrete time'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Discrete time"

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Zhu, Gaoyan, Lei Xiao, Bingzi Huo, and Peng Xue. "Photonic discrete-time quantum walks [Invited]." Chinese Optics Letters 18, no. 5 (2020): 052701. http://dx.doi.org/10.3788/col202018.052701.

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Richman, M. S., T. W. Parks, and R. G. Shenoy. "Discrete-time, discrete-frequency, time-frequency analysis." IEEE Transactions on Signal Processing 46, no. 6 (June 1998): 1517–27. http://dx.doi.org/10.1109/78.678465.

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P., Tymoshchuk. "SIMPLIFIED PARALLEL SORTING DISCRETE-TIME NEURAL NETWORK MODEL." Computer systems and network 2, no. 1 (March 23, 2017): 94–101. http://dx.doi.org/10.23939/csn2020.01.094.

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A model of parallel sorting neural network of discrete-time has been proposed. The model is described by system of difference equations and by step functions. The model is based on simplified neural circuit of discrete-time that identifies maximal/minimal values of input data and is described by difference equation and by step functions. A bound from above on a number of iterations required for reaching convergence of search process to steady state is determined. The model does not need a knowledge of change range of input data. In order to use the model a minimal difference between values of input data should be known. The network can process unknown input data with finite values, located in arbitrary unknown finite range. The network is characterized by moderate computational complexity and complexity of software implementation, any finite resolution of input data, speed,. Computing simulation results illustrating efficiency of the network are given. Keywords — Parallel sorting, neural network, difference equation, computational complexity, hardware implementation.
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Else, Dominic V., Christopher Monroe, Chetan Nayak, and Norman Y. Yao. "Discrete Time Crystals." Annual Review of Condensed Matter Physics 11, no. 1 (March 10, 2020): 467–99. http://dx.doi.org/10.1146/annurev-conmatphys-031119-050658.

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Experimental advances have allowed for the exploration of nearly isolated quantum many-body systems whose coupling to an external bath is very weak. A particularly interesting class of such systems is those that do not thermalize under their own isolated quantum dynamics. In this review, we highlight the possibility for such systems to exhibit new nonequilibrium phases of matter. In particular, we focus on discrete time crystals, which are many-body phases of matter characterized by a spontaneously broken discrete time-translation symmetry. We give a definition of discrete time crystals from several points of view, emphasizing that they are a nonequilibrium phenomenon that is stabilized by many-body interactions, with no analog in noninteracting systems. We explain the theory behind several proposed models of discrete time crystals, and compare several recent realizations, in different experimental contexts.
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Ramakalyan, A., P. Kavitha, and S. Harini Vijayalakshmi. "Discrete-time systems." Resonance 5, no. 4 (April 2000): 91–96. http://dx.doi.org/10.1007/bf02837910.

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Ramakalyan, A., P. Kavitha, and S. Harini Vijayalakshmi. "Discrete-time systems." Resonance 5, no. 2 (February 2000): 39–49. http://dx.doi.org/10.1007/bf02838822.

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Khan, A. R., F. Mehmood, and M. A. Shaikh. "Обобщение неравенств Островского на временных шкалах." Владикавказский математический журнал 25, no. 3 (September 25, 2023): 98–110. http://dx.doi.org/10.46698/q4172-3323-1923-j.

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The idea of time scales calculus’ theory was initiated and introduced by Hilger (1988) in his PhD thesis order to unify discret and continuous analysis and to expend the discrete and continous theories to cases ``in between''. Since then, mathematical research in this field has exceeded more than 1000 publications and a lot of applications in the fields of science, i.e., operations research, economics, physics, engineering, statistics, finance and biology. Ostrowski proved an inequality to estimate the absolute deviation of a differentiable function from its integral mean. This result was obtained by applying the Montgomery identity. In the present paper we derive a generalization of the Montgomery identity to the various time scale versions such as discrete case, continuous case and the case of quantum calculus, by obtaining this generalization of Montgomery identity we would prove our results about the generalization of the Ostrowski inequalities (without weighted case) to the several time scales such as discrete case, continuous case and the case of quantum calculus and recapture the several published results of different authors of various papers and thus unify corresponding discrete version and continuous version. Similarly we would also derive our results about the generalization of the Ostrowski inequalities (weighted case) to the different time scales such as discrete case and continuous case and recapture the different published results of several authors of various papers and thus unify corresponding discrete version and continuous version. Moreover, we would use our obtained results (without weighted case) to the case of quantum calculus.
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Mostafa, El-Sayed M. E. "COMPUTATIONAL DESIGN OF OPTIMAL DISCRETE-TIME OUTPUT FEEDBACK CONTROLLERS." Journal of the Operations Research Society of Japan 51, no. 1 (2008): 15–28. http://dx.doi.org/10.15807/jorsj.51.15.

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FRYZ, Mykhailo, and Bogdana MLYNKO. "DISCRETE-TIME CONDITIONAL LINEAR RANDOM PROCESSES AND THEIR PROPERTIES." Herald of Khmelnytskyi National University. Technical sciences 309, no. 3 (May 26, 2022): 7–12. http://dx.doi.org/10.31891/2307-5732-2022-309-3-7-12.

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Continuous-time conditional linear random process is represented as a stochastic integral of a random kernel driven by a process with independent increments. Such processes are used in the problems of mathematical modelling, computer simulation, and processing of stochastic signals, the physical nature of which generates them to be represented as the sum of many random impulses that occur at Poisson moments. Impulses are stochastically dependent functions, in contrast to another well-known mathematical model which is a linear random process, that has a similar structure but is represented as the sum of a large amount of independent random impulses that occur at Poisson moments of time. The application areas of these models are mathematical modelling, computer simulation, and processing of electroencephalographic signals, cardio signals, resource consumption processes (such as electricity consumption, water consumption, gas consumption), radar signals, etc. A discrete-time conditional linear random process has been defined in the paper, the relationships with corresponding continuous-time model has been shown. According to the given definition the discrete-time conditional linear random process can be considered as an output of linear digital filter with random parameters on the input of the white noise which is infinitely divisible distributed. Moment functions of first and second order have been analyzed. In particular, the expressions for mathematical expectation, variance and covariance function have been obtained. The results can be utilized to study the probabilistic characteristics of the investigated information stochastic signals, which will depend on the properties of the corresponding kernel and white noise. In particular, the conditions for the process to be wide-sense stationary have been represented.
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Peyrin, F., and R. Prost. "A unified definition for the discrete-time, discrete-frequency, and discrete-time/Frequency Wigner distributions." IEEE Transactions on Acoustics, Speech, and Signal Processing 34, no. 4 (August 1986): 858–67. http://dx.doi.org/10.1109/tassp.1986.1164880.

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Dissertations / Theses on the topic "Discrete time"

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Said, Maya Rida 1976. "Discrete-time randomized sampling." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/86836.

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Wild, Marie. "Characterizing discrete time function spaces." [S.l.] : [s.n.], 2006. http://mediatum2.ub.tum.de/doc/602043/document.pdf.

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Petersson, Mikael. "Perturbed discrete time stochastic models." Doctoral thesis, Stockholms universitet, Matematiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-128979.

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In this thesis, nonlinearly perturbed stochastic models in discrete time are considered. We give algorithms for construction of asymptotic expansions with respect to the perturbation parameter for various quantities of interest. In particular, asymptotic expansions are given for solutions of renewal equations, quasi-stationary distributions for semi-Markov processes, and ruin probabilities for risk processes.

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4: Manuscript. Paper 5: Manuscript. Paper 6: Manuscript.

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Holm, Jens Christian. "Spinors in discrete space-time." Thesis, Georgia Institute of Technology, 1985. http://hdl.handle.net/1853/27901.

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OLIVEIRA, HUGO DE SOUZA. "DISCRETE TIME FINITE MARKET MODEL." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=32298@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO
O trabalho tem como objetivo ser uma introdução ao estudo de mercados financeiros tratados em tempo discreto com horizonte finito, bem como a dinâmica dos ativos financeiros principais. Descrevemos os tipos de ativos negociados em nosso mercado, dando enfoque aos contratos. Elaboraremos a hipótese central do modelo, a ausência de arbitragem e assim mostraremos como poderemos encontrar um preço correto ou então apresentaremos um intervalo de preços para os contratos. Posteriormente, mostraremos resultados gerais relativos à correta precificação de contratos, usando para isso os instrumentos de processos estocásticos e martingais. Apresentaremos alguns exemplos a título de ilustração.
The dissertation aims to be an introduction to the study of financial markets in discrete time with finite horizon, as well as the dynamics of the main financial assets. We describe the types of assets traded in the market, focusing on contracts. We will elaborate the central hypothesis of the model, the absence of arbitrage and thus show how we can find a correct price or, at least, a range of prices of the contracts. Subsequently, we will show general results regarding how to find correct prices for contracts, using the machinery of stochastic processes and martingales.As an illustration, we present some examples.
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Hazell, Andrew. "Discrete-time optimal preview control." Thesis, Imperial College London, 2008. http://hdl.handle.net/10044/1/8472.

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There are many situations in which one can preview future reference signals, or future disturbances. Optimal Preview Control is concerned with designing controllers which use this preview to improve closed-loop performance. In this thesis a general preview control problem is presented which includes previewable disturbances, dynamic weighting functions, output feedback and nonpreviewable disturbances. It is then shown how a variety of problems may be cast as special cases of this general problem; of particular interest is the robust preview tracking problem and the problem of disturbance rejection with uncertainty in the previewed signal. The general preview problem is solved in both the Fh and Beo settings. The H2 solution is a relatively straightforward extension ofpreviously known results, however, our contribution is to provide a single framework that may be used as a reference work when tackling a variety of preview problems. We also provide some new analysis concerning the maximum possible reduction in closed-loop H2 norm which accrues from the addition of preview action. The solution to the Hoo problem involves a completely new approach to Hoo preview control, in which the structure of the associated Riccati equation is exploited in order to find an efficient algorithm for computing the optimal controller. The problem tackled here is also more generic than those previously appearing in the literature. The above theory finds obvious applications in the design of controllers for autonomous vehicles, however, a particular class of nonlinearities found in typical vehicle models presents additional problems. The final chapters are concerned with a generic framework for implementing vehicle preview controllers, and also a'case study on preview control of a bicycle.
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Jerbi, Ali. "Adaptive control of time-varying discrete-time systems." Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/15743.

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Poufinas, Thomas. "Discrete-Time and Continuous-Time Option Pricing with Fees /." The Ohio State University, 1996. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487934589977028.

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Schweighofer, Marc C. "Projecting COSAGE output in discrete time." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1999. http://handle.dtic.mil/100.2/ADA381212.

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Thesis (M.S. in Operations Research) Naval Postgraduate School, December 1999.
Thesis advisors, Donald P. Gaver, Patricia A. Jacobs. Includes bibliographical references (p. 91). Also available online.
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Walker, Daniel James. "Robust control of discrete time systems." Thesis, Imperial College London, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321140.

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Books on the topic "Discrete time"

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Zhang, Kuize, Lijun Zhang, and Lihua Xie. Discrete-Time and Discrete-Space Dynamical Systems. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-25972-3.

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Discrete-time control systems. Englewood Cliffs, N.J: Prentice-Hall, 1987.

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Guex, Jean, Federico Galster, and Øyvind Hammer. Discrete Biochronological Time Scales. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-21326-2.

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Söderström, T. Discrete-time Stochastic Systems. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0101-7.

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Williamson, Darrell. Discrete-time Signal Processing. London: Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0541-1.

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Alfa, Attahiru S. Applied Discrete-Time Queues. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3420-1.

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Abidi, Khalid, and Jian-Xin Xu. Advanced Discrete-Time Control. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-287-478-8.

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Gu, Guoxiang. Discrete-Time Linear Systems. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-2281-5.

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Discrete-time control systems. Englewood Cliffs: Prentice-Hall, 1987.

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Oppenheim, Alan V. Discrete-time signal processing. 3rd ed. Upper Saddle River, New Jersey: Pearson, 2010.

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Book chapters on the topic "Discrete time"

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Privault, Nicolas. "Discrete-Time Martingales." In Springer Undergraduate Mathematics Series, 263–80. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0659-4_10.

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Sengupta, Jati K., and Phillip Fanchon. "Discrete time models." In Control Theory Methods in Economics, 63–96. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6285-6_3.

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Jackson, Leland B. "Discrete-Time Networks." In Digital Filters and Signal Processing, 95–137. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4757-2458-5_5.

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Peters, Marc A., and Pablo A. Iglesias. "Discrete-Time Entropy." In Systems & Control: Foundations & Applications, 46–68. Boston, MA: Birkhäuser Boston, 1997. http://dx.doi.org/10.1007/978-1-4612-1982-8_4.

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Bosq, Denis, and Hung T. Nguyen. "Discrete-Time Martingales." In A Course in Stochastic Processes, 219–32. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-015-8769-3_11.

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Röman, Jan R. M. "Time-Discrete Models." In Analytical Finance: Volume I, 21–89. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-34027-2_2.

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Kaeding, Matthias. "Discrete Time Models." In Bayesian Analysis of Failure Time Data Using P-Splines, 45–59. Wiesbaden: Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-08393-9_4.

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Law, Kody, Andrew Stuart, and Konstantinos Zygalakis. "Discrete Time: Formulation." In Data Assimilation, 25–52. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20325-6_2.

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Nagurney, Anna, and Ding Zhang. "Discrete Time Algorithms." In Projected Dynamical Systems and Variational Inequalities with Applications, 75–90. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-2301-7_4.

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Ryan, Øyvind. "Discrete Time Filters." In Springer Undergraduate Texts in Mathematics and Technology, 93–139. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-01812-2_3.

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Conference papers on the topic "Discrete time"

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KHRENNIKOV, A., and Ya VOLOVICH. "DISCRETE ENERGY SPECTRUM IN DISCRETE TIME DYNAMICS." In Proceedings of the 26th Conference. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812770271_0029.

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Einicke, Garry. "Discrete-time Smoothing Formulas." In TENCON 2005 - 2005 IEEE Region 10 Conference. IEEE, 2005. http://dx.doi.org/10.1109/tencon.2005.301074.

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Sola, Manuel A., and Sebastia Sallent-Ribes. "Discrete-time wavelet transform." In SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, edited by Andrew F. Laine and Michael A. Unser. SPIE, 1995. http://dx.doi.org/10.1117/12.217634.

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Touri, B., and A. Nedic. "Discrete-time opinion dynamics." In 2011 45th Asilomar Conference on Signals, Systems and Computers. IEEE, 2011. http://dx.doi.org/10.1109/acssc.2011.6190199.

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Juan, Y. C., and P. T. Kabamba. "Optimal Discrete Time Tracking." In 1989 American Control Conference. IEEE, 1989. http://dx.doi.org/10.23919/acc.1989.4790460.

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Gargantini, A., and A. Morzenti. "Automated Verification of Continuous Time Systems by Discrete Temporal Induction." In Thirteenth International Symposium on Temporal Representation and Reasoning (TIME'06). IEEE, 2006. http://dx.doi.org/10.1109/time.2006.8.

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Jian, Sun, Wang Yan, and Ze-bin Zhao. "Discrete-time Risk Measures with Time Consistency." In 2006 International Conference on Management Science and Engineering. IEEE, 2006. http://dx.doi.org/10.1109/icmse.2006.313855.

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Adamiak, Katarzyna. "Time-Variant Discrete-Time Sliding Mode Control." In 2021 22nd International Carpathian Control Conference (ICCC). IEEE, 2021. http://dx.doi.org/10.1109/iccc51557.2021.9454639.

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Amato, F., M. Carbone, M. Ariola, and C. Cosentino. "Finite-time stability of discrete-time systems." In Proceedings of the 2004 American Control Conference. IEEE, 2004. http://dx.doi.org/10.23919/acc.2004.1386778.

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Almeida, Joao, Carlos Silvestre, Antonio M. Pascoal, and Panos J. Antsaklis. "Continuous-time consensus with discrete-time communication." In 2009 European Control Conference (ECC). IEEE, 2009. http://dx.doi.org/10.23919/ecc.2009.7074493.

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Reports on the topic "Discrete time"

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Campos, Sergio V., and Edmund M. Clarke. Real-Time Symbolic Model Checking for Discrete Time Models. Fort Belvoir, VA: Defense Technical Information Center, May 1994. http://dx.doi.org/10.21236/ada282878.

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Backus, David, Silverio Foresi, and Chris Telmer. Discrete-Time Models of Bond Pricing. Cambridge, MA: National Bureau of Economic Research, September 1998. http://dx.doi.org/10.3386/w6736.

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Cambanis, Stamatis, and Elias Masry. Performance of Discrete-Time Predictors of Continuous-Time Stationary Processes. Fort Belvoir, VA: Defense Technical Information Center, December 1985. http://dx.doi.org/10.21236/ada166231.

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Savov, Svetoslav, and Ivan Popchev. Stability Tests for Discrete-time Polytopic Systems. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, September 2018. http://dx.doi.org/10.7546/crabs.2018.09.10.

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Shum, A. Discrete-Time Analysis of an ATM Multiplexer. Fort Belvoir, VA: Defense Technical Information Center, September 1995. http://dx.doi.org/10.21236/ada302230.

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Stoffer, David S. Walsh-Fourier Analysis of Discrete-Valued Time Series. Fort Belvoir, VA: Defense Technical Information Center, November 1985. http://dx.doi.org/10.21236/ada166139.

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Fox, Bennett L., and Peter W. Glynn. Discrete-Time Conversion for Simulating Finite-Horizon Markov Processes. Fort Belvoir, VA: Defense Technical Information Center, May 1989. http://dx.doi.org/10.21236/ada210683.

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Houdre, Christian, and Benjamin Kedem. On Autocovariance Estimation for Discrete Spectrum Stationary Time Series. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada455033.

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Baker, Charles R. Coding Capacity of Discrete-Time Gaussian and Nongaussian Channels. Fort Belvoir, VA: Defense Technical Information Center, October 1987. http://dx.doi.org/10.21236/ada190318.

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Wong-Toi, Howard, and Gerard Hoffmann. The Control of Dense Real-Time Discrete Event Systems,. Fort Belvoir, VA: Defense Technical Information Center, March 1992. http://dx.doi.org/10.21236/ada325997.

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