Calculus for Cognitive Scientists Higher Order Models and Their Analysis

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.

Über den Autor / die Autorin

Dr. James Peterson is an Associate Professor in Mathematical Sciences and Biological Sciences at Clemson University, USA. His formal training is in mathematics but he has worked as an aerospace engineer and a software engineer also. He enjoys working on very hard problems that require multiple disciplines to make sense out of and he reads, studies and plays in cutting edge areas a lot as part of his interests.

Zusammenfassung

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.

Produktdetails

• Autoren: James Peterson, James K. Peterson, James K Peterson
• Verlag: Springer, Berlin
• Inhalt: Buch
• Produktform: Fester Einband
• Erscheinungsdatum: 31.01.2016
• Thema: Naturwissenschaften, Medizin, Informatik, Technik > Technik > Allgemeines, Lexika
• EAN: 9789812878755
• ISBN: 978-981-287-875-5
• Anzahl Seiten: 556
• Illustration: XXXIII, 556 p. 135 illus., 115 illus. in color.
• Abmessung (Verpackung): 16.7 x 24 x 3.6 cm
• Gewicht (Verpackung): 988 g
• Serie: Cognitive Science and Technology; Cognitive Science and Technology
• Themen: B, Artificial Intelligence, Mathematische Physik, Bildverarbeitung, Mathematische Modellierung, engineering, Computer Vision, Computer Imaging, Vision, Pattern Recognition and Graphics, Theoretical, Mathematical and Computational Physics, Mathematical physics, Computational Intelligence, Optical data processing, Mathematical modelling, Image processing, Neural networks (Computer science)