Calculus for Cognitive Scientists : Partial Differential Equation Models
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The work Calculus for Cognitive Scientists : Partial Differential Equation Models represents a distinct intellectual or artistic creation found in Boston University Libraries. This resource is a combination of several types including: Work, Language Material, Books.
The Resource
Calculus for Cognitive Scientists : Partial Differential Equation Models
Resource Information
The work Calculus for Cognitive Scientists : Partial Differential Equation Models represents a distinct intellectual or artistic creation found in Boston University Libraries. This resource is a combination of several types including: Work, Language Material, Books.
 Label
 Calculus for Cognitive Scientists : Partial Differential Equation Models
 Title remainder
 Partial Differential Equation Models
 Statement of responsibility
 by James K. Peterson
 Subject

 Computer Imaging, Vision, Pattern Recognition and Graphics
 Computational Intelligence
 Computer graphics
 Computational intelligence
 Theoretical, Mathematical and Computational Physics
 Engineering
 Physics
 Neural networks (Computer science)
 Computational intelligence
 Neural networks (Computer science)
 Computational Intelligence
 Computer graphics
 Electronic resources
 Mathematical Models of Cognitive Processes and Neural Networks
 Computational intelligence
 Engineering
 Engineering
 Artificial intelligence
 Computational Intelligence
 Artificial intelligence
 Artificial intelligence
 Physics
 Computer graphics
 Physics
 Neural networks (Computer science)
 Artificial Intelligence (incl. Robotics)
 Language
 eng
 Summary
 This book shows cognitive scientists in training how mathematics, computerÂ science and science can be usefully and seamlessly intertwined. It is a followup to the first two volumes on mathematics for cognitive scientists, and includes the mathematics and computational tools needed to understand how to compute the terms in the Fourier series expansions that solve the cable equation. The latter is derived from first principles by going back to cellular biology and the relevantÂ biophysics.Â A detailed discussion of ion movementÂ through cellular membranes, and an explanation of how the equations that govern such ion movement leading to the standard transient cable equation are included. There are also solutions for the cable model using separation of variables, as well an explanation of why Fourier series converge and a description of the implementation of MatLab tools to compute the solutions. Finally, the standard Hodgkin  Huxley model is developedÂ forÂ an excitable neuron and is solved using MatLab
 Image bit depth
 0
 LC call number
 Q342
 Literary form
 non fiction
 Series statement
 Cognitive Science and Technology,
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