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Journal articles on the topic 'Semi-linear'

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1

Georgiou, Nicos, Mathew Joseph, Davar Khoshnevisan, and Shang-Yuan Shiu. "Semi-discrete semi-linear parabolic SPDEs." Annals of Applied Probability 25, no. 5 (October 2015): 2959–3006. http://dx.doi.org/10.1214/14-aap1065.

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2

BAME, Valmir, and Lulezim HANELLI. "Numerical Solution for Semi Linear Hyperbolic Differential Equations." International Journal of Innovative Research in Engineering & Management 6, no. 4 (July 2019): 28–32. http://dx.doi.org/10.21276/ijirem.2019.6.4.1.

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3

Krief, Jerome M. "Semi‐linear mode regression." Econometrics Journal 20, no. 2 (June 1, 2017): 149–67. http://dx.doi.org/10.1111/ectj.12088.

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4

Knüppel, Frieder, and Klaus Nielsen. "Covering singular linear semi-groups." Linear Algebra and its Applications 438, no. 7 (April 2013): 3039–53. http://dx.doi.org/10.1016/j.laa.2012.12.005.

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5

Aneiros-Pérez, Germán, and Philippe Vieu. "Semi-functional partial linear regression." Statistics & Probability Letters 76, no. 11 (June 2006): 1102–10. http://dx.doi.org/10.1016/j.spl.2005.12.007.

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6

Lin, C. J., S. C. Fang, and Soon-Yi Wu. "Parametric linear semi-infinite programming." Applied Mathematics Letters 9, no. 3 (May 1996): 89–96. http://dx.doi.org/10.1016/0893-9659(96)00038-9.

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7

Altman, Eitan. "Semi-linear Stochastic Difference Equations." Discrete Event Dynamic Systems 19, no. 1 (October 23, 2008): 115–36. http://dx.doi.org/10.1007/s10626-008-0053-4.

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8

Liu, Chien-Liang, Wen-Hoar Hsaio, Chia-Hoang Lee, and Fu-Sheng Gou. "Semi-Supervised Linear Discriminant Clustering." IEEE Transactions on Cybernetics 44, no. 7 (July 2014): 989–1000. http://dx.doi.org/10.1109/tcyb.2013.2278466.

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9

Toher, Deirdre, Gerard Downey, and Thomas Brendan Murphy. "Semi-supervised linear discriminant analysis." Journal of Chemometrics 25, no. 12 (November 10, 2011): 621–30. http://dx.doi.org/10.1002/cem.1408.

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10

D’Alessandro, Flavio, Benedetto Intrigila, and Stefano Varricchio. "Quasi-polynomials, linear Diophantine equations and semi-linear sets." Theoretical Computer Science 416 (January 2012): 1–16. http://dx.doi.org/10.1016/j.tcs.2011.10.014.

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11

Mabrouk, M., and H. Samadi. "Linear and semi-linear reinforcement problems by thin layers." Zeitschrift f�r Angewandte Mathematik und Physik (ZAMP) 54, no. 2 (March 1, 2003): 349–75. http://dx.doi.org/10.1007/s000330300008.

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12

Maz'ya, Vladimir, and Valdimir Karlin. "Semi-analytic time-marching algorithms for semi-linear parabolic equations." BIT 34, no. 1 (March 1994): 129–47. http://dx.doi.org/10.1007/bf01935022.

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13

Dongshuang, Zhang. "Semi-linear Elliptic Equations on Graph." Journal of Partial Differential Equations 30, no. 3 (June 2017): 221–31. http://dx.doi.org/10.4208/jpde.v30.n3.3.

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14

Gutlyanski, Vladimir, Olga Nesmelova, and Vladimir Ryazanov. "Semi-linear equations and quasiconformal mappings." Complex Variables and Elliptic Equations 65, no. 5 (October 15, 2019): 823–43. http://dx.doi.org/10.1080/17476933.2019.1631288.

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15

Qingguo, Tang. "Estimation for semi-functional linear regression." Statistics 49, no. 6 (November 20, 2014): 1262–78. http://dx.doi.org/10.1080/02331888.2014.979827.

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16

Knuth, Donald E. "Semi-optimal bases for linear dependencies." Linear and Multilinear Algebra 17, no. 1 (January 1985): 1–4. http://dx.doi.org/10.1080/03081088508817636.

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17

Álvarez, Teresa, Sonia Keskes, and Maher Mnif. "On essentially semi regular linear relations." Linear Algebra and its Applications 530 (October 2017): 518–40. http://dx.doi.org/10.1016/j.laa.2017.06.017.

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18

Ding, Hui, Zhiping Lu, Jian Zhang, and Riquan Zhang. "Semi-functional partial linear quantile regression." Statistics & Probability Letters 142 (November 2018): 92–101. http://dx.doi.org/10.1016/j.spl.2018.07.007.

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19

Brannigan, M. "Approximation by semi-non-linear functions." Journal of Approximation Theory 48, no. 2 (October 1986): 189–200. http://dx.doi.org/10.1016/0021-9045(86)90003-1.

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20

Chan-Wai-Nam, Quentin, Joseph Mikael, and Xavier Warin. "Machine Learning for Semi Linear PDEs." Journal of Scientific Computing 79, no. 3 (February 12, 2019): 1667–712. http://dx.doi.org/10.1007/s10915-019-00908-3.

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21

Dorsey, Jonathan, Tom Gannon, Nathaniel Jacobson, Charles R. Johnson, and Morrison Turnansky. "Linear preservers of semi-positive matrices." Linear and Multilinear Algebra 64, no. 9 (December 22, 2015): 1853–62. http://dx.doi.org/10.1080/03081087.2015.1122723.

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22

Strauss, H. "Uniqueness in Linear Semi-infinite Optimization." Journal of Approximation Theory 75, no. 2 (November 1993): 198–213. http://dx.doi.org/10.1006/jath.1993.1099.

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23

Fougères, P., and B. Zegarliński. "Semi-linear problems in infinite dimensions." Journal of Functional Analysis 228, no. 1 (November 2005): 39–88. http://dx.doi.org/10.1016/j.jfa.2005.06.019.

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24

Zhang, Qinghong. "Understanding linear semi-infinite programming via linear programming over cones." Optimization 59, no. 8 (November 2010): 1247–58. http://dx.doi.org/10.1080/02331930903395865.

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25

Nicolas, Jean-Philippe, and Truong Xuan Pham. "Peeling on Kerr Spacetime: Linear and Semi-linear Scalar Fields." Annales Henri Poincaré 20, no. 10 (August 21, 2019): 3419–70. http://dx.doi.org/10.1007/s00023-019-00832-0.

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26

Ziemian, Bogdan. "Mean value theorems for linear and semi-linear rotation invariant operators." Annales Polonici Mathematici 51, no. 1 (1990): 341–48. http://dx.doi.org/10.4064/ap-51-1-341-348.

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27

Debrabant, Kristian, and Espen R. Jakobsen. "Semi-Lagrangian schemes for linear and fully non-linear diffusion equations." Mathematics of Computation 82, no. 283 (December 20, 2012): 1433–62. http://dx.doi.org/10.1090/s0025-5718-2012-02632-9.

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28

Sophocleous, C., and R. Tracinà. "Differential invariants for quasi-linear and semi-linear wave-type equations." Applied Mathematics and Computation 202, no. 1 (August 2008): 216–28. http://dx.doi.org/10.1016/j.amc.2008.01.033.

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29

Pandit, Purnima K. "Exact Solution of Semi-linear Fuzzy System." Journal of the Indian Mathematical Society 84, no. 3-4 (July 1, 2017): 225. http://dx.doi.org/10.18311/jims/2017/15569.

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In this paper we consider a semi-linear dynamical system with fuzzy initial condition. We discuss the results regarding the existence of the solution and obtain the best possible solution for such systems. We give a real life supportive illustration of population model, justify the need for fuzzy setup for the problem, and discuss the solution for it.
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30

Millard, Salomon M., and Frans H. J. Kanfer. "Mixtures of Semi-Parametric Generalised Linear Models." Symmetry 14, no. 2 (February 18, 2022): 409. http://dx.doi.org/10.3390/sym14020409.

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The mixture of generalised linear models (MGLM) requires knowledge about each mixture component’s specific exponential family (EF) distribution. This assumption is relaxed and a mixture of semi-parametric generalised linear models (MSPGLM) approach is proposed, which allows for unknown distributions of the EF for each mixture component while much of the parametric structure of the traditional MGLM is retained. Such an approach inherently allows for both symmetric and non-symmetric component distributions, frequently leading to non-symmetrical response variable distributions. It is assumed that the random component of each mixture component follows an unknown distribution of the EF. The specific member can either be from the standard class of distributions or from the broader set of admissible distributions of the EF which is accessible through the semi-parametric procedure. Since the inverse link functions of the mixture components are unknown, the MSPGLM estimates each mixture component’s inverse link function using a kernel smoother. The MSPGLM algorithm alternates the estimation of the regression parameters with the estimation of the inverse link functions. The properties of the proposed MSPGLM are illustrated through a simulation study on the separable individual components. The MSPGLM procedure is also applied on two data sets.
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31

Wu, Yaoqiang. "On (fuzzy) pseudo-semi-normed linear spaces." AIMS Mathematics 7, no. 1 (2021): 467–77. http://dx.doi.org/10.3934/math.2022030.

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<abstract><p>In this paper, we introduce the notion of pseudo-semi-normed linear spaces, following the concept of pseudo-norm which was presented by Schaefer and Wolff, and illustrate their relationship. On the other hand, we introduce the concept of fuzzy pseudo-semi-norm, which is weaker than the notion of fuzzy pseudo-norm initiated by N$ \tilde{\rm{a}} $d$ \tilde{\rm{a}} $ban. Moreover, we give some examples which are according to the commonly used $ t $-norms. Finally, we establish norm structures of fuzzy pseudo-semi-normed spaces and provide (fuzzy) topological spaces induced by (fuzzy) pseudo-semi-norms, and prove that the (fuzzy) topological spaces are (fuzzy) Hausdorff.</p></abstract>
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32

Shustin, Paz Fink, and Haim Avron. "Semi-Infinite Linear Regression and Its Applications." SIAM Journal on Matrix Analysis and Applications 43, no. 1 (March 2022): 479–511. http://dx.doi.org/10.1137/21m1411950.

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33

Atia, M. J. "Semi-Classical Linear Functionals and Integral Representation." Integral Transforms and Special Functions 14, no. 1 (February 2003): 59–67. http://dx.doi.org/10.1080/10652460304542.

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34

Li, Meng-Rong. "ON THE SEMI-LINEAR WAVE EQUATIONS (I)." Taiwanese Journal of Mathematics 2, no. 3 (September 1998): 329–45. http://dx.doi.org/10.11650/twjm/1500406973.

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35

Gómez †, Juan A., Paul J. Bosch ‡, and Jorge Amaya. "Duality for inexact semi-infinite linear programming." Optimization 54, no. 1 (February 2005): 1–25. http://dx.doi.org/10.1080/02331930412331286595.

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36

KUNIMATSU, NOBORU, and HIDEKI SANO. "Compensator design of semi-linear parabolic systems." International Journal of Control 60, no. 2 (August 1994): 243–63. http://dx.doi.org/10.1080/00207179408921463.

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37

Molchanov, Ilya, Vadim Shcherbakov, and Sergei Zuyev. "Critical growth of a semi-linear process." Journal of Applied Probability 41, no. 2 (June 2004): 355–67. http://dx.doi.org/10.1239/jap/1082999071.

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This paper is motivated by the modelling of leaching of bacteria through soil. A semi-linear process Xt− may be used to describe the soil-drying process between rain showers. This is a backward recurrence time process that corresponds to the renewal process of instances of rain. If a bacterium moves according to another process h, then the fact that h(t) stays above Xt− means that the bacterium never hits a dry patch of soil and so survives. We describe a critical behaviour of h that separates the cases when survival is possible with a positive probability from the cases when this probability vanishes. An explicit formula for the survival probability is obtained in case h is linear and rain showers follow a Poisson process.
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38

Schraudolph, Nicol N., Martin Eldracher, and Jürgen Schmidhuber. "Processing images by semi-linear predictability minimization." Network: Computation in Neural Systems 10, no. 2 (January 1999): 133–69. http://dx.doi.org/10.1088/0954-898x_10_2_303.

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39

Cánovas, M. J., A. Y. Kruger, M. A. López, J. Parra, and M. A. Théra. "Calmness Modulus of Linear Semi-infinite Programs." SIAM Journal on Optimization 24, no. 1 (January 2014): 29–48. http://dx.doi.org/10.1137/130907008.

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40

Tapia Cuitiño, Luis Felipe, and Andrea Luigi Tironi. "Dual codes of product semi-linear codes." Linear Algebra and its Applications 457 (September 2014): 114–53. http://dx.doi.org/10.1016/j.laa.2014.05.011.

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41

Blömker, Dirk, Giuseppe Cannizzaro, and Marco Romito. "Random initial conditions for semi-linear PDEs." Proceedings of the Royal Society of Edinburgh: Section A Mathematics 150, no. 3 (January 29, 2019): 1533–65. http://dx.doi.org/10.1017/prm.2018.157.

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AbstractWe analyse the effect of random initial conditions on the local well-posedness of semi-linear PDEs, to investigate to what extent recent ideas on singular stochastic PDEs can prove useful in this framework.In particular, in some cases, stochastic initial conditions extend the validity of the fixed-point argument to larger spaces than deterministic initial conditions would allow, but in general, it is never possible to go beyond the threshold that is predicted by critical scaling, as in our general class of equations we are not exploiting any special structure present in the equation.We also give a specific example where the level of regularity for the fixed-point argument reached by random initial conditions is not yet critical, but it is already sharp in the sense that we find infinitely many random initial conditions of slightly lower regularity, where there is no solution at all. Thus criticality cannot be reached even by random initial conditions.The existence and uniqueness in a critical space is always delicate, but we can consider the Burgers equation in logarithmically sub-critical spaces, where existence and uniqueness hold, and again random initial conditions allow to extend the validity to spaces of lower regularity which are still logarithmically sub-critical.
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42

Wang, Feizhi, and Yisheng Huang. "On a semi-linear Schrödinger equation in." Nonlinear Analysis: Theory, Methods & Applications 62, no. 5 (August 2005): 833–48. http://dx.doi.org/10.1016/j.na.2005.03.087.

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43

Goberna, M. A., and M. A. López. "Optimality theory for semi-infinite linear programming∗." Numerical Functional Analysis and Optimization 16, no. 5-6 (January 1995): 669–700. http://dx.doi.org/10.1080/01630569508816638.

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44

Zhou, Jianjun, and Min Chen. "Spline estimators for semi-functional linear model." Statistics & Probability Letters 82, no. 3 (March 2012): 505–13. http://dx.doi.org/10.1016/j.spl.2011.11.027.

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45

Molchanov, Ilya, Vadim Shcherbakov, and Sergei Zuyev. "Critical growth of a semi-linear process." Journal of Applied Probability 41, no. 02 (June 2004): 355–67. http://dx.doi.org/10.1017/s0021900200014352.

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This paper is motivated by the modelling of leaching of bacteria through soil. A semi-linear process X t − may be used to describe the soil-drying process between rain showers. This is a backward recurrence time process that corresponds to the renewal process of instances of rain. If a bacterium moves according to another process h, then the fact that h(t) stays above X t − means that the bacterium never hits a dry patch of soil and so survives. We describe a critical behaviour of h that separates the cases when survival is possible with a positive probability from the cases when this probability vanishes. An explicit formula for the survival probability is obtained in case h is linear and rain showers follow a Poisson process.
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46

Pühl, H., and W. Schirotzek. "Linear semi-openness and the Lyusternik theorem." European Journal of Operational Research 157, no. 1 (August 2004): 16–27. http://dx.doi.org/10.1016/j.ejor.2003.08.011.

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47

Mawhin, J., J. R. Ward, and M. Willem. "Variational methods and semi-linear elliptic equations." Archive for Rational Mechanics and Analysis 95, no. 3 (September 1986): 269–77. http://dx.doi.org/10.1007/bf00251362.

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48

Friz, Peter, and Harald Oberhauser. "Rough path stability of (semi-)linear SPDEs." Probability Theory and Related Fields 158, no. 1-2 (February 8, 2013): 401–34. http://dx.doi.org/10.1007/s00440-013-0483-2.

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49

Goberna, M. A. "Boundedness relations in linear semi-infinite programming." Advances in Applied Mathematics 8, no. 1 (March 1987): 53–68. http://dx.doi.org/10.1016/0196-8858(87)90005-4.

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50

Ghate, Archis. "Inverse optimization in semi-infinite linear programs." Operations Research Letters 48, no. 3 (May 2020): 278–85. http://dx.doi.org/10.1016/j.orl.2020.02.007.

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