Academic literature on the topic 'Stochastic Differential Algebraic Equations'

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Journal articles on the topic "Stochastic Differential Algebraic Equations"

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Thi The, Nguyen. "Stochastic Differential Algebraic Equations of Index 2." Lobachevskii Journal of Mathematics 45, no. 12 (2024): 6569–80. https://doi.org/10.1134/s1995080224606726.

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Higueras, I., J. Moler, F. Plo, and M. San Miguel. "Urn models and differential algebraic equations." Journal of Applied Probability 40, no. 2 (2003): 401–12. http://dx.doi.org/10.1239/jap/1053003552.

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The aim of this paper is to study the distribution of colours, {Xn}, in a generalized Pólya urn model with L colours, an urn function and a random environment. In this setting, the number of actions to be taken can be greater than L, and the total number of balls added in each step can be random. The process {Xn} is expressed as a stochastic recurrent equation that fits a Robbins—Monro scheme. Since this process evolves in the (L—1)-simplex, the stability of the solutions of the ordinary differential equation associated with the Robbins—Monro scheme can be studied by means of differential alge
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Higueras, I., J. Moler, F. Plo, and M. San Miguel. "Urn models and differential algebraic equations." Journal of Applied Probability 40, no. 02 (2003): 401–12. http://dx.doi.org/10.1017/s0021900200019380.

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The aim of this paper is to study the distribution of colours, { X n }, in a generalized Pólya urn model with L colours, an urn function and a random environment. In this setting, the number of actions to be taken can be greater than L, and the total number of balls added in each step can be random. The process { X n } is expressed as a stochastic recurrent equation that fits a Robbins—Monro scheme. Since this process evolves in the (L—1)-simplex, the stability of the solutions of the ordinary differential equation associated with the Robbins—Monro scheme can be studied by means of differentia
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Alabert, Aureli, and Marco Ferrante. "Linear stochastic differential-algebraic equations with constant coefficients." Electronic Communications in Probability 11 (2006): 316–35. http://dx.doi.org/10.1214/ecp.v11-1236.

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Li, Xun, Jingtao Shi, and Jiongmin Yong. "Mean-field linear-quadratic stochastic differential games in an infinite horizon." ESAIM: Control, Optimisation and Calculus of Variations 27 (2021): 81. http://dx.doi.org/10.1051/cocv/2021078.

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This paper is concerned with two-person mean-field linear-quadratic non-zero sum stochastic differential games in an infinite horizon. Both open-loop and closed-loop Nash equilibria are introduced. The existence of an open-loop Nash equilibrium is characterized by the solvability of a system of mean-field forward-backward stochastic differential equations in an infinite horizon and the convexity of the cost functionals, and the closed-loop representation of an open-loop Nash equilibrium is given through the solution to a system of two coupled non-symmetric algebraic Riccati equations. The exis
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CONG, NGUYEN DINH, and NGUYEN THI THE. "LYAPUNOV SPECTRUM OF NONAUTONOMOUS LINEAR STOCHASTIC DIFFERENTIAL ALGEBRAIC EQUATIONS OF INDEX-1." Stochastics and Dynamics 12, no. 04 (2012): 1250002. http://dx.doi.org/10.1142/s0219493712500025.

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We introduce a concept of Lyapunov exponents and Lyapunov spectrum of a stochastic differential algebraic equation (SDAE) of index-1. The Lyapunov exponents are defined samplewise via the induced two-parameter stochastic flow generated by inherent regular stochastic differential equations. We prove that Lyapunov exponents are nonrandom.
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Lv, Xueqin, and Jianfang Gao. "Treatment for third-order nonlinear differential equations based on the Adomian decomposition method." LMS Journal of Computation and Mathematics 20, no. 1 (2017): 1–10. http://dx.doi.org/10.1112/s1461157017000018.

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The Adomian decomposition method (ADM) is an efficient method for solving linear and nonlinear ordinary differential equations, differential algebraic equations, partial differential equations, stochastic differential equations, and integral equations. Based on the ADM, a new analytical and numerical treatment is introduced in this research for third-order boundary-value problems. The effectiveness of the proposed approach is verified by numerical examples.
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Drăgan, Vasile, Ivan Ganchev Ivanov, and Ioan-Lucian Popa. "A Game — Theoretic Model for a Stochastic Linear Quadratic Tracking Problem." Axioms 12, no. 1 (2023): 76. http://dx.doi.org/10.3390/axioms12010076.

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In this paper, we solve a stochastic linear quadratic tracking problem. The controlled dynamical system is modeled by a system of linear Itô differential equations subject to jump Markov perturbations. We consider the case when there are two decision-makers and each of them wants to minimize the deviation of a preferential output of the controlled dynamical system from a given reference signal. We assume that the two decision-makers do not cooperate. Under these conditions, we state the considered tracking problem as a problem of finding a Nash equilibrium strategy for a stochastic differentia
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Pulch, Roland. "Stochastic collocation and stochastic Galerkin methods for linear differential algebraic equations." Journal of Computational and Applied Mathematics 262 (May 2014): 281–91. http://dx.doi.org/10.1016/j.cam.2013.10.046.

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Curry, Charles, Kurusch Ebrahimi–Fard, Simon J. A. Malham, and Anke Wiese. "Algebraic structures and stochastic differential equations driven by Lévy processes." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 475, no. 2221 (2019): 20180567. http://dx.doi.org/10.1098/rspa.2018.0567.

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We construct an efficient integrator for stochastic differential systems driven by Lévy processes. An efficient integrator is a strong approximation that is more accurate than the corresponding stochastic Taylor approximation, to all orders and independent of the governing vector fields. This holds provided the driving processes possess moments of all orders and the vector fields are sufficiently smooth. Moreover, the efficient integrator in question is optimal within a broad class of perturbations for half-integer global root mean-square orders of convergence. We obtain these results using th
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Dissertations / Theses on the topic "Stochastic Differential Algebraic Equations"

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Curry, Charles. "Algebraic structures in stochastic differential equations." Thesis, Heriot-Watt University, 2014. http://hdl.handle.net/10399/2791.

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We define a new numerical integration scheme for stochastic differential equations driven by Levy processes with uniformly lower mean square remainder than that of the scheme of the same strong order of convergence obtained by truncating the stochastic Taylor series. In doing so we generalize recent results concerning stochastic differential equations driven by Wiener processes. The aforementioned works studied integration schemes obtained by applying an invertible mapping to the stochastic Taylor series, truncating the resulting series and applying the inverse of the original mapping. The shu
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Dabrowski, Yoann. "Free entropies, free Fisher information, free stochastic differential equations, with applications to Von Neumann algebras." Thesis, Paris Est, 2010. http://www.theses.fr/2010PEST1015.

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Ce travail étend nos connaissances des entropies libres et des équations différentielles stochastiques (EDS) libres dans trois directions. Dans un premier temps, nous montrons que l'algèbre de von Neumann engendrée par au moins deux autoadjoints ayant une information de Fisher finie n'a pas la propriété $Gamma$ de Murray et von Neumann. C'est un analogue d'un résultat de Voiculescu pour l'entropie microcanonique libre. Dans un second temps, nous étudions des EDS libres à coefficients opérateurs non-bornés (autrement dit des sortes d' EDP stochastiques libres ). Nous montrons la stationnarité d
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Ding, Jie. "Structural and fluid analysis for large scale PEPA models, with applications to content adaptation systems." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/7975.

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The stochastic process algebra PEPA is a powerful modelling formalism for concurrent systems, which has enjoyed considerable success over the last decade. Such modelling can help designers by allowing aspects of a system which are not readily tested, such as protocol validity and performance, to be analysed before a system is deployed. However, model construction and analysis can be challenged by the size and complexity of large scale systems, which consist of large numbers of components and thus result in state-space explosion problems. Both structural and quantitative analysis of large scale
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Tribastone, Mirco. "Scalable analysis of stochastic process algebra models." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4629.

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The performance modelling of large-scale systems using discrete-state approaches is fundamentally hampered by the well-known problem of state-space explosion, which causes exponential growth of the reachable state space as a function of the number of the components which constitute the model. Because they are mapped onto continuous-time Markov chains (CTMCs), models described in the stochastic process algebra PEPA are no exception. This thesis presents a deterministic continuous-state semantics of PEPA which employs ordinary differential equations (ODEs) as the underlying mathematics for the p
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Bringuier, Hugo. "Marches quantiques ouvertes." Thesis, Toulouse 3, 2018. http://www.theses.fr/2018TOU30064/document.

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Cette thèse est consacrée à l'étude de modèles stochastiques associés aux systèmes quantiques ouverts. Plus particulièrement, nous étudions les marches quantiques ouvertes qui sont les analogues quantiques des marches aléatoires classiques. La première partie consiste en une présentation générale des marches quantiques ouvertes. Nous présentons les outils mathématiques nécessaires afin d'étudier les systèmes quantiques ouverts, puis nous exposons les modèles discrets et continus des marches quantiques ouvertes. Ces marches sont respectivement régies par des canaux quantiques et des opérateurs
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Trenn, Stephan. "Distributional differential algebraic equations." Ilmenau Univ.-Verl, 2009. http://d-nb.info/99693197X/04.

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Bahar, Arifah. "Applications of stochastic differential equations and stochastic delay differential equations in population dynamics." Thesis, University of Strathclyde, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.415294.

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Dareiotis, Anastasios Constantinos. "Stochastic partial differential and integro-differential equations." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/14186.

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In this work we present some new results concerning stochastic partial differential and integro-differential equations (SPDEs and SPIDEs) that appear in non-linear filtering. We prove existence and uniqueness of solutions of SPIDEs, we give a comparison principle and we suggest an approximation scheme for the non-local integral operators. Regarding SPDEs, we use techniques motivated by the work of De Giorgi, Nash, and Moser, in order to derive global and local supremum estimates, and a weak Harnack inequality.
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Abourashchi, Niloufar. "Stability of stochastic differential equations." Thesis, University of Leeds, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.509828.

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Zhang, Qi. "Stationary solutions of stochastic partial differential equations and infinite horizon backward doubly stochastic differential equations." Thesis, Loughborough University, 2008. https://dspace.lboro.ac.uk/2134/34040.

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In this thesis we study the existence of stationary solutions for stochastic partial differential equations. We establish a new connection between solutions of backward doubly stochastic differential equations (BDSDEs) on infinite horizon and the stationary solutions of the SPDEs. For this, we prove the existence and uniqueness of the L2ρ (Rd; R1) × L2ρ (Rd; Rd) valued solutions of BDSDEs with Lipschitz nonlinear term on both finite and infinite horizons, so obtain the solutions of initial value problems and the stationary weak solutions (independent of any initial value) of SPDEs. Also the L2
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Books on the topic "Stochastic Differential Algebraic Equations"

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Vârsan, Constantin. Applications of Lie algebras to hyperbolic and stochastic differential equations. Kluwer Academic Publishers, 1999.

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Øksendal, Bernt. Stochastic Differential Equations. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-662-02847-6.

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Øksendal, Bernt. Stochastic Differential Equations. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-03185-8.

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Øksendal, Bernt. Stochastic Differential Equations. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-14394-6.

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Panik, Michael J. Stochastic Differential Equations. John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119377399.

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Øksendal, Bernt. Stochastic Differential Equations. Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-662-13050-6.

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Øksendal, Bernt. Stochastic Differential Equations. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-662-02574-1.

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Sobczyk, Kazimierz. Stochastic Differential Equations. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3712-6.

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Cecconi, Jaures, ed. Stochastic Differential Equations. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-11079-5.

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Øksendal, Bernt. Stochastic Differential Equations. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-03620-4.

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Book chapters on the topic "Stochastic Differential Algebraic Equations"

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Winkler, R. "Stochastic Differential Algebraic Equations in Transient Noise Analysis." In Scientific Computing in Electrical Engineering. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-32862-9_22.

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Ocone, Daniel, and Etienne Pardoux. "A Lie algebraic criterion for non-existence of finite dimensionally computable filters." In Stochastic Partial Differential Equations and Applications II. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/bfb0083947.

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Vârsan, Constantin. "Finitely Generated over Orbits Lie Algebras and Algebraic Representation of the Gradient System." In Applications of Lie Algebras to Hyperbolic and Stochastic Differential Equations. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4679-1_4.

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Janowicz, Maciej, Joanna Kaleta, Filip Krzyżewski, Marian Rusek, and Arkadiusz Orłowski. "Homotopy Analysis Method for Stochastic Differential Equations with Maxima." In Computer Algebra in Scientific Computing. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24021-3_18.

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Vârsan, Constantin. "Gradient Systems in a Lie Algebra." In Applications of Lie Algebras to Hyperbolic and Stochastic Differential Equations. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4679-1_2.

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Kulasiri, Don. "Wick Algebra, Diffusions, and Computations." In Stochastic Differential Equations for Chemical Transformations in White Noise Probability Space. Springer Nature Singapore, 2024. https://doi.org/10.1007/978-981-97-9392-1_3.

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Vârsan, Constantin. "Introduction." In Applications of Lie Algebras to Hyperbolic and Stochastic Differential Equations. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4679-1_1.

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Vârsan, Constantin. "Representation of a Gradient System." In Applications of Lie Algebras to Hyperbolic and Stochastic Differential Equations. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4679-1_3.

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Vârsan, Constantin. "Applications." In Applications of Lie Algebras to Hyperbolic and Stochastic Differential Equations. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4679-1_5.

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Vârsan, Constantin. "Stabilization and Related Problems." In Applications of Lie Algebras to Hyperbolic and Stochastic Differential Equations. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4679-1_6.

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Conference papers on the topic "Stochastic Differential Algebraic Equations"

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Rupsys, Petras. "STOCHASTIC SIMULATION OF SELF-THINNING." In 24th SGEM International Multidisciplinary Scientific GeoConference 2024. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024/3.1/s14.46.

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Understanding the principles of self-thinning forest ecosystems is essential for taking modern management techniques into practice. The spatial distribution of the surviving trees in a stand is influenced by a variety of factors, including tree mortality. In young forests, competition has a major role in determining spatial mortality; in older forests, random changes in the environment have a major role. The dynamics of the number of living and dead trees in the forests of central Lithuania will be addressed in this study. The Gompertz type mixed effect parameters univariate stochastic differe
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Chen, Yahao, and Stephan Trenn. "Solution concepts for linear piecewise affine differential-algebraic equations." In 2024 IEEE 63rd Conference on Decision and Control (CDC). IEEE, 2024. https://doi.org/10.1109/cdc56724.2024.10885793.

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Gerdin, Markus, and Johan Sjoberg. "Nonlinear Stochastic Differential-Algebraic Equations with Application to Particle Filtering." In Proceedings of the 45th IEEE Conference on Decision and Control. IEEE, 2006. http://dx.doi.org/10.1109/cdc.2006.377135.

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HUDSON, R. L. "ALGEBRAIC STOCHASTIC DIFFERENTIAL EQUATIONS AND A FUBINI THEOREM FOR SYMMETRISED DOUBLE QUANTUM STOCHASTIC PRODUCT INTEGRALS." In Proceedings of the Third International Conference. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812810267_0007.

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Bereza, Robert, Oscar Eriksson, Mohamed R. H. Abdalmoaty, David Broman, and Hakan Hjalmarsson. "Stochastic Approximation for Identification of Non-Linear Differential-Algebraic Equations with Process Disturbances." In 2022 IEEE 61st Conference on Decision and Control (CDC). IEEE, 2022. http://dx.doi.org/10.1109/cdc51059.2022.9993085.

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Zhou, Bo, Ruiwei Jiang, and Siqian Shen. "Differential-Algebraic Equation-Constrained Frequency-Secured Stochastic Unit Commitment." In 2023 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2023. http://dx.doi.org/10.1109/pesgm52003.2023.10253174.

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Wang, Keyou, and Mariesa L. Crow. "Numerical simulation of Stochastic Differential Algebraic Equations for power system transient stability with random loads." In 2011 IEEE Power & Energy Society General Meeting. IEEE, 2011. http://dx.doi.org/10.1109/pes.2011.6039188.

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MALGRANGE, B. "DIFFERENTIAL ALGEBRAIC GROUPS." In Algebraic Approach to Differential Equations. WORLD SCIENTIFIC, 2010. http://dx.doi.org/10.1142/9789814273244_0007.

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Acciarini, Giacomo, Nicola Baresi, David Lloyd, and Dario Izzo. "Stochastic Continuation for Space Trajectory Design." In ESA 12th International Conference on Guidance Navigation and Control and 9th International Conference on Astrodynamics Tools and Techniques. ESA, 2023. http://dx.doi.org/10.5270/esa-gnc-icatt-2023-198.

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Designing and planning periodic orbits in an uncertain environment can be very challenging. Traditionally, trajectories are engineered in a two-step approach. First, nominal orbits are designed, describing the system as a deterministic dynamical model. Then, brute-force Monte Carlo simulations are used to test the initial conditions against model uncertainties and knowledge errors (e.g. imprecise estimation of the spacecraft state). While this approach constitutes the de facto standard in current space trajectory design practices, it leads to very time consuming and potentially suboptimal solu
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Bostan, Alin, Frédéric Chyzak, Bruno Salvy, Grégoire Lecerf, and Éric Schost. "Differential equations for algebraic functions." In the 2007 international symposium. ACM Press, 2007. http://dx.doi.org/10.1145/1277548.1277553.

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Reports on the topic "Stochastic Differential Algebraic Equations"

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Gear, C. W. Differential algebraic equations, indices, and integral algebraic equations. Office of Scientific and Technical Information (OSTI), 1989. http://dx.doi.org/10.2172/6307619.

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Knorrenschild, M. Differential-algebraic equations as stiff ordinary differential equations. Office of Scientific and Technical Information (OSTI), 1989. http://dx.doi.org/10.2172/6980335.

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Yan, Xiaopu. Singularly Perturbed Differential/Algebraic Equations. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada288365.

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Ashby, S. F., S. L. Lee, L. R. Petzold, P. E. Saylor, and E. Seidel. Computing spacetime curvature via differential-algebraic equations. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/221033.

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Rabier, Patrick J., and Werner C. Rheinboldt. On Impasse Points of Quasilinear Differential Algebraic Equations. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada252643.

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Rabier, Patrick J., and Werner C. Rheinboldt. A Geometric Treatment of Implicit Differential-Algebraic Equations. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada236991.

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Christensen, S. K., and G. Kallianpur. Stochastic Differential Equations for Neuronal Behavior. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada159099.

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Ober, Curtis C., Roscoe Bartlett, Todd S. Coffey, and Roger P. Pawlowski. Rythmos: Solution and Analysis Package for Differential-Algebraic and Ordinary-Differential Equations. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1364461.

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Dalang, Robert C., and N. Frangos. Stochastic Hyperbolic and Parabolic Partial Differential Equations. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada290372.

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Jiang, Bo, Roger Brockett, Weibo Gong, and Don Towsley. Stochastic Differential Equations for Power Law Behaviors. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada577839.

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