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Titlebook: Calculus for Cognitive Scientists; Higher Order Models James K. Peterson Book 2016 Springer Science+Business Media Singapore 2016 Antideri

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樓主: Johnson
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發(fā)表于 2025-3-23 13:21:49 | 只看該作者
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發(fā)表于 2025-3-23 17:50:38 | 只看該作者
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發(fā)表于 2025-3-23 18:21:49 | 只看該作者
Predator–Prey Modelsolution and satisfies a type of nonlinear conservation law. MatLab tools specialized for this model are also introduced. It also shows how this model, adjusted for fishing rates, helps to explain fishery catch data from World War I.
14#
發(fā)表于 2025-3-23 23:23:31 | 只看該作者
Nonlinear Differential Equationsnd an related linear system of ODE governed by the linear dynamics determined by the Jacobian at the given equilibrium. The overall system is then understood by piecing together the individual linear approximate systems. New MatLab tools are developed to generate the various phase plane plots required to understand what the trajectories are doing.
15#
發(fā)表于 2025-3-24 03:48:59 | 只看該作者
Book 2016s on two variable ODE models, both linear and nonlinear, and highlights theoretical and computational tools using MATLAB to explain their solutions. It also shows how to solve cable models using separation of variables and the Fourier Series..
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發(fā)表于 2025-3-24 08:32:38 | 只看該作者
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發(fā)表于 2025-3-24 12:20:25 | 只看該作者
Cognitive Science and Technologyhttp://image.papertrans.cn/c/image/220868.jpg
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發(fā)表于 2025-3-24 18:53:47 | 只看該作者
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發(fā)表于 2025-3-24 19:11:01 | 只看該作者
Pierre Baldi,Yves Chauvin,Van Mittal-HenkleThis chapter discusses numerical methods for first order ODEs and includes a careful derivation of the error estimates for Euler’s method. It includes a review of function approximation tools. It reviews Runge–Kutta methods as well and discusses the MatLab implementation of both methods.
20#
發(fā)表于 2025-3-24 23:36:31 | 只看該作者
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