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The Resource Calculus for Cognitive Scientists : Partial Differential Equation Models, by James K. Peterson, (electronic resource)
Calculus for Cognitive Scientists : Partial Differential Equation Models, by James K. Peterson, (electronic resource)
Resource Information
The item Calculus for Cognitive Scientists : Partial Differential Equation Models, by James K. Peterson, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.This item is available to borrow from all library branches.
Resource Information
The item Calculus for Cognitive Scientists : Partial Differential Equation Models, by James K. Peterson, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.
This item is available to borrow from all library branches.
 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
 Language
 eng
 Edition
 1st ed. 2016.
 Extent
 XXXI, 534 p. 156 illus. in color.
 Contents

 Introduction
 Graham  Schmidt Orthogonalization
 Numerical Diï¬erential Equations
 Biological Molecules
 Ion Movement
 Lumped and Distributed Cell Models
 Time Independent Solutions to Inï¬nite Cables
 Time Independent Solutions to Finite and HalfInï¬nite Space Cables
 A Primer On Series Solutions
 Linear Partial Diï¬erential Equations
 Simpliï¬ed Dendrite  Soma â Axon Information Processing
 The Basic Hodgkin  Huxley Model
 Final Thoughts
 Background Reading
 Isbn
 9789812878809
 Label
 Calculus for Cognitive Scientists : Partial Differential Equation Models
 Title
 Calculus for Cognitive Scientists
 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
 http://library.link/vocab/creatorName
 Peterson, James K
 Image bit depth
 0
 LC call number
 Q342
 Literary form
 non fiction
 http://library.link/vocab/relatedWorkOrContributorName
 SpringerLink
 Series statement
 Cognitive Science and Technology,
 http://library.link/vocab/subjectName

 Engineering
 Artificial intelligence
 Computer graphics
 Neural networks (Computer science)
 Physics
 Computational intelligence
 Engineering
 Computational Intelligence
 Theoretical, Mathematical and Computational Physics
 Mathematical Models of Cognitive Processes and Neural Networks
 Artificial Intelligence (incl. Robotics)
 Computer Imaging, Vision, Pattern Recognition and Graphics
 Label
 Calculus for Cognitive Scientists : Partial Differential Equation Models, by James K. Peterson, (electronic resource)
 Antecedent source
 mixed
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents
 Introduction  Graham  Schmidt Orthogonalization  Numerical Diï¬erential Equations  Biological Molecules  Ion Movement  Lumped and Distributed Cell Models  Time Independent Solutions to Inï¬nite Cables  Time Independent Solutions to Finite and HalfInï¬nite Space Cables  A Primer On Series Solutions  Linear Partial Diï¬erential Equations  Simpliï¬ed Dendrite  Soma â Axon Information Processing  The Basic Hodgkin  Huxley Model  Final Thoughts  Background Reading
 Dimensions
 unknown
 Edition
 1st ed. 2016.
 Extent
 XXXI, 534 p. 156 illus. in color.
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9789812878809
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Other control number
 10.1007/9789812878809
 Other physical details
 online resource.
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number
 (DEHe213)9789812878809
 Label
 Calculus for Cognitive Scientists : Partial Differential Equation Models, by James K. Peterson, (electronic resource)
 Antecedent source
 mixed
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents
 Introduction  Graham  Schmidt Orthogonalization  Numerical Diï¬erential Equations  Biological Molecules  Ion Movement  Lumped and Distributed Cell Models  Time Independent Solutions to Inï¬nite Cables  Time Independent Solutions to Finite and HalfInï¬nite Space Cables  A Primer On Series Solutions  Linear Partial Diï¬erential Equations  Simpliï¬ed Dendrite  Soma â Axon Information Processing  The Basic Hodgkin  Huxley Model  Final Thoughts  Background Reading
 Dimensions
 unknown
 Edition
 1st ed. 2016.
 Extent
 XXXI, 534 p. 156 illus. in color.
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9789812878809
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Other control number
 10.1007/9789812878809
 Other physical details
 online resource.
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number
 (DEHe213)9789812878809
Subject
 Artificial Intelligence (incl. Robotics)
 Artificial intelligence
 Artificial intelligence
 Artificial intelligence
 Computational Intelligence
 Computational Intelligence
 Computational Intelligence
 Computational intelligence
 Computational intelligence
 Computational intelligence
 Computer Imaging, Vision, Pattern Recognition and Graphics
 Computer graphics
 Computer graphics
 Computer graphics
 Electronic resources
 Engineering
 Engineering
 Engineering
 Mathematical Models of Cognitive Processes and Neural Networks
 Neural networks (Computer science)
 Neural networks (Computer science)
 Neural networks (Computer science)
 Physics
 Physics
 Physics
 Theoretical, Mathematical and Computational Physics
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