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Calculus for Cognitive Scientists [electronic resource] : Higher Order Models and Their Analysis / by James K. Peterson.

By: Contributor(s): Material type: TextSeries: Cognitive Science and TechnologyPublisher: Singapore : Springer Singapore : Imprint: Springer, 2016Edition: 1st ed. 2016Description: XXXIII, 556 p. 135 illus., 115 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9789812878779
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.3 23
Online resources:
Contents:
Introductory Remarks -- Linear Algebra -- Numerical Methods Order One ODEs -- Multivariable Calculus -- Integration -- Complex Numbers -- Linear Second Order ODEs -- Systems -- Numerical Methods Systems of ODEs -- Predator Prey Models -- Predator Prey Models With Self Interaction -- Disease Models -- A Cancer Model -- Nonlinear Differential Equations -- An Insulin Model -- Series Solutions -- Final Thoughts -- Background Reading.
In: Springer eBooksSummary: This book offers a self-study program on how mathematics, computer science and science can be profitably and seamlessly intertwined. This book focuses 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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Introductory Remarks -- Linear Algebra -- Numerical Methods Order One ODEs -- Multivariable Calculus -- Integration -- Complex Numbers -- Linear Second Order ODEs -- Systems -- Numerical Methods Systems of ODEs -- Predator Prey Models -- Predator Prey Models With Self Interaction -- Disease Models -- A Cancer Model -- Nonlinear Differential Equations -- An Insulin Model -- Series Solutions -- Final Thoughts -- Background Reading.

This book offers a self-study program on how mathematics, computer science and science can be profitably and seamlessly intertwined. This book focuses 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.