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Search results for: PARAMETER
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 10 m, q = 90 deg, j = 45 deg, a =4 m, e = 8, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 200 m, q = 90 deg, j = 135 deg, a =4 m, e = 4, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 200 m, q = 80 deg, j = 45 deg, a =4 m, e = 8, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 20 m, q = 100 deg, j = 45 deg, a =4 m, e = 8, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 20 m, q = 80 deg, j = 135 deg, a =4 m, e = 1, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 10 m, q = 80 deg, j = 135 deg, a =4 m, e = 1, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 10 m, q = 100 deg, j = 135 deg, a =4 m, e = 4, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 50 m, q = 90 deg, j = 135 deg, a =4 m, e = 4, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 10 m, q = 80 deg, j = 45 deg, a =4 m, e = 8, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 20 m, q = 80 deg, j = 135 deg, a =4 m, e = 4, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 100 m, q = 100 deg, j = 135 deg, a =4 m, e = 4, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 50 m, q = 90 deg, j = 45 deg, a =4 m, e = 8, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 200 m, q = 90 deg, j = 45 deg, a =4 m, e = 8, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 20 m, q = 90 deg, j = 135 deg, a =4 m, e = 1, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 10 m, q = 100 deg, j = 45 deg, a =4 m, e = 8, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 100 m, q = 80 deg, j = 135 deg, a =4 m, e = 4, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 200 m, q = 80 deg, j = 135 deg, a =4 m, e = 1, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 100 m, q = 90 deg, j = 45 deg, a =4 m, e = 8, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 200 m, q = 90 deg, j = 135 deg, a =4 m, e = 1, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 10 m, q = 80 deg, j = 135 deg, a =4 m, e = 4, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Description of symmetrical prolate ellipsoid magnetic signature parameters-Be = 50 mT, I = 70 deg, z = 20 m, q = 90 deg, j = 45 deg, a =4 m, e = 8, mr = 100
Open Research DataThe Earth magnetic field (Fig.1): BE – total magnetic flux density, BEx – x component of the Earth magnetic flux density, BEy = 0 y component of the Earth magnetic flux density, BEz – z component of the Earth magnetic flux density, I – inclination of the Earth magnetic field.
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Stochastic intervals for the family of quadratic maps
Open Research DataNumerical analysis of chaotic dynamics is a challenging task. The one-parameter families of logistic maps and closely related quadratic maps f_a(x)=a-x^2 are well-known examples of such dynamical systems. Determining parameter values that yield stochastic-like dynamics is especially difficult, because although this set has positive Lebesgue measure,...
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Uniform expansion estimates in the quadratic map as a function of the partition size, using Johnson’s algorithm
Open Research DataThis dataset contains selected results of numerical computations described in the paper "Quantitative hyperbolicity estimates in one-dimensional dynamics" by S. Day, H. Kokubu, S. Luzzatto, K. Mischaikow, H. Oka, P. Pilarczyk, published in Nonlinearity, Vol. 21, No. 9 (2008), 1967-1987, doi: 10.1088/0951-7715/21/9/002.
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Uniform expansion estimates in the quadratic map with the smallest critical neighborhood for which the expansion exponent λ0 is positive
Open Research DataThis dataset contains selected results of numerical computations described in the paper "Quantitative hyperbolicity estimates in one-dimensional dynamics" by S. Day, H. Kokubu, S. Luzzatto, K. Mischaikow, H. Oka, P. Pilarczyk, published in Nonlinearity, Vol. 21, No. 9 (2008), 1967-1987, doi: 10.1088/0951-7715/21/9/002.
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Uniform expansion estimates in the quadratic map as a function of the partition size, computing λ only
Open Research DataThis dataset contains selected results of numerical computations described in the paper "Quantitative hyperbolicity estimates in one-dimensional dynamics" by S. Day, H. Kokubu, S. Luzzatto, K. Mischaikow, H. Oka, P. Pilarczyk, published in Nonlinearity, Vol. 21, No. 9 (2008), 1967-1987, doi: 10.1088/0951-7715/21/9/002.
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Uniform expansion estimates in the quadratic map as a function of the partition size, using the “derivative” partition type
Open Research DataThis dataset contains selected results of numerical computations described in the paper "Quantitative hyperbolicity estimates in one-dimensional dynamics" by S. Day, H. Kokubu, S. Luzzatto, K. Mischaikow, H. Oka, P. Pilarczyk, published in Nonlinearity, Vol. 21, No. 9 (2008), 1967-1987, doi: 10.1088/0951-7715/21/9/002.
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Uniform expansion estimates in the quadratic map with the smallest critical neighborhood for which the expansion exponent λ is positive
Open Research DataThis dataset contains selected results of numerical computations described in the paper "Quantitative hyperbolicity estimates in one-dimensional dynamics" by S. Day, H. Kokubu, S. Luzzatto, K. Mischaikow, H. Oka, P. Pilarczyk, published in Nonlinearity, Vol. 21, No. 9 (2008), 1967-1987, doi: 10.1088/0951-7715/21/9/002.
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Uniform expansion estimates in the quadratic map as a function of the critical neighborhood size
Open Research DataThis dataset contains selected results of numerical computations described in the paper "Quantitative hyperbolicity estimates in one-dimensional dynamics" by S. Day, H. Kokubu, S. Luzzatto, K. Mischaikow, H. Oka, P. Pilarczyk, published in Nonlinearity, Vol. 21, No. 9 (2008), 1967-1987, doi: 10.1088/0951-7715/21/9/002.
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Uniform expansion estimates in the quadratic map as a function of the partition size, using the “critical” partition type
Open Research DataThis dataset contains selected results of numerical computations described in the paper "Quantitative hyperbolicity estimates in one-dimensional dynamics" by S. Day, H. Kokubu, S. Luzzatto, K. Mischaikow, H. Oka, P. Pilarczyk, published in Nonlinearity, Vol. 21, No. 9 (2008), 1967-1987, doi: 10.1088/0951-7715/21/9/002.
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Uniform expansion estimates in the quadratic map as a function of the partition size, using the Floyd–Warshall algorithm
Open Research DataThis dataset contains selected results of numerical computations described in the paper "Quantitative hyperbolicity estimates in one-dimensional dynamics" by S. Day, H. Kokubu, S. Luzzatto, K. Mischaikow, H. Oka, P. Pilarczyk, published in Nonlinearity, Vol. 21, No. 9 (2008), 1967-1987, doi: 10.1088/0951-7715/21/9/002.
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Uniform expansion estimates in the quadratic map with the smallest critical neighborhood for which the expansion exponent λ0 is greater than 0.1
Open Research DataThis dataset contains selected results of numerical computations described in the paper "Quantitative hyperbolicity estimates in one-dimensional dynamics" by S. Day, H. Kokubu, S. Luzzatto, K. Mischaikow, H. Oka, P. Pilarczyk, published in Nonlinearity, Vol. 21, No. 9 (2008), 1967-1987, doi: 10.1088/0951-7715/21/9/002.
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Uniform expansion estimates in the quadratic map with the smallest critical neighborhood for which the expansion exponent λ is greater than 0.1
Open Research DataThis dataset contains selected results of numerical computations described in the paper "Quantitative hyperbolicity estimates in one-dimensional dynamics" by S. Day, H. Kokubu, S. Luzzatto, K. Mischaikow, H. Oka, P. Pilarczyk, published in Nonlinearity, Vol. 21, No. 9 (2008), 1967-1987, doi: 10.1088/0951-7715/21/9/002.
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Morse decompositions for a two-dimensional discrete neuron model (low resolution)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
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Morse decompositions for a two-dimensional discrete neuron model (limited range)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
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Morse decompositions for a two-dimensional discrete neuron model (full range)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
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Recurrence times in the Morse sets for a two-dimensional discrete neuron model (low resolution)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
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Morse decompositions for a two-patch vaccination model
Open Research DataThis dataset contains selected results of rigorous numerical computations described in Section 5 of the paper "Rich bifurcation structure in a two-patch vaccination model" by D.H. Knipl, P. Pilarczyk, G. Röst, published in SIAM Journal on Applied Dynamical Systems (SIADS), Vol. 14, No. 2 (2015), pp. 980–1017, doi: 10.1137/140993934.
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X-ray diffractometry results of the Sr0.86Ti0.65Fe0.35O3 powder
Open Research DataThis dataset contains results of X-ray diffractometry mesurement (XRD) of the Sr0.86Ti0.65Fe0.35O3-d (STF35) powder. The phase composition of the investigated STF35 powder was analyzed by XRD at room temperature. It confirms the formation of the cubic perovskite oxide phase. Calculated average lattice constant is a 3.90882(1) Å, with Goodness of Fit...
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The Weibull model of the multipath fading channel
Open Research DataThe dataset contains the results of simulations that are part of the research on modelling the multipath fading in the communication channel. The Weibull fading envelope is generated using the Monte-Carlo simulation (MCS) in the LabVIEW programming environment.
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Sound signals generated during lapping of technical ceramics using electroplated tools with diamond grains
Open Research DataData contains the recordings of sound generated during single-sided lapping with the use of electroplated diamond tools. This relationship was examined with the use of spectral analysis of the sound signal in the frequency domain with a focus on the Ra parameter of the surface roughness. The estimated sound coefficient increased as the surface roughness...
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Continuation classes for a two-patch vaccination model
Open Research DataThis dataset contains selected results of rigorous numerical computations described in Section 5 of the paper "Rich bifurcation structure in a two-patch vaccination model" by D.H. Knipl, P. Pilarczyk, G. Röst, published in SIAM Journal on Applied Dynamical Systems (SIADS), Vol. 14, No. 2 (2015), pp. 980–1017, doi: 10.1137/140993934.
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The generalized Suzuki model of the multipath fading channel
Open Research DataThe dataset contains the results of simulations that are part of the research on modelling the multipath fading in the communication channel. The generalized Suzuki fading envelope is generated using the Monte-Carlo simulation (MCS) in the LabVIEW programming environment.
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Conley-Morse graphs for a two-patch vaccination model
Open Research DataThis dataset contains selected results of rigorous numerical computations described in Section 5 of the paper "Rich bifurcation structure in a two-patch vaccination model" by D.H. Knipl, P. Pilarczyk, G. Röst, published in SIAM Journal on Applied Dynamical Systems (SIADS), Vol. 14, No. 2 (2015), pp. 980–1017, doi: 10.1137/140993934.
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Determination of the effective concentration of ketoprofen against the germination of Sorghum bicolor (sorghum) seeds
Open Research DataResearch data includes an attempt to determine the effective concentration of ketoprofen that inhibits germination of Sorghum bicolor (sorghum) seeds.
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Conley-Morse graphs for a two-dimensional discrete neuron model (low resolution)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
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Conley-Morse graphs for a two-dimensional discrete neuron model (limited range)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
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Conley-Morse graphs for a two-dimensional discrete neuron model (full range)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
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Continuation classes for a population model with harvesting. Case He-S1: Equal harvesting of juveniles and adults, survival rates of juveniles and adults add up to 1
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper "Global dynamics in a stage-structured discrete population model with harvesting" by E. Liz and P. Pilarczyk: Journal of Theoretical Biology, Vol. 297 (2012), pp. 148–165, doi: 10.1016/j.jtbi.2011.12.012.
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Continuation classes for a population model with harvesting. Case Ha-S1: Harvesting adults only, survival rates of juveniles and adults add up to 1
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper "Global dynamics in a stage-structured discrete population model with harvesting" by E. Liz and P. Pilarczyk: Journal of Theoretical Biology, Vol. 297 (2012), pp. 148–165, doi: 10.1016/j.jtbi.2011.12.012.
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Continuation classes for a population model with harvesting. Case He-Se: Equal harvesting and equal survival rates of juveniles and adults
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper "Global dynamics in a stage-structured discrete population model with harvesting" by E. Liz and P. Pilarczyk: Journal of Theoretical Biology, Vol. 297 (2012), pp. 148–165, doi: 10.1016/j.jtbi.2011.12.012.