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03412nam a22005415i 4500 |
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978-981-287-871-7 |
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DE-He213 |
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20160212021150.0 |
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cr nn 008mamaa |
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160210s2016 si | s |||| 0|eng d |
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|a 9789812878717
|9 978-981-287-871-7
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|a 10.1007/978-981-287-871-7
|2 doi
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|d GrThAP
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|a Q342
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|a COM004000
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|a Peterson, James K.
|e author.
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|a BioInformation Processing
|h [electronic resource] :
|b A Primer on Computational Cognitive Science /
|c by James K. Peterson.
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| 250 |
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|a 1st ed. 2016.
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| 264 |
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|a Singapore :
|b Springer Singapore :
|b Imprint: Springer,
|c 2016.
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| 300 |
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|a XXXV, 570 p. 165 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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|a Cognitive Science and Technology,
|x 2195-3988
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|a BioInformation Processing -- The Diffusion Equation -- Integral Transforms -- The Time Dependent Cable Solution -- Mammalian Neural Structure -- Abstracting Principles of Computation -- Abstracting Principles of Computation -- Second Messenger Diffusion Pathways -- The Abstract Neuron Model -- Emotional Models -- Generation of Music Data: J. Peterson and L. Dzuris -- Generation of Painting Data: J. Peterson, L. Dzuris and Q. Peterson -- Modeling Compositional Design -- Networks Of Excitable Neurons -- Training The Model -- Matrix Feed Forward Networks -- Chained Feed Forward Architectures -- Graph Models -- Address Based Graphs -- Building Brain Models -- Models of Cognitive Dysfunction -- Conclusions -- Background Reading.
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|a This book shows how mathematics, computer science and science can be usefully and seamlessly intertwined. It begins with a general model of cognitive processes in a network of computational nodes, such as neurons, using a variety of tools from mathematics, computational science and neurobiology. It then moves on to solve the diffusion model from a low-level random walk point of view. It also demonstrates how this idea can be used in a new approach to solving the cable equation, in order to better understand the neural computation approximations. It introduces specialized data for emotional content, which allows a brain model to be built using MatLab tools, and also highlights a simple model of cognitive dysfunction.
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|a Engineering.
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| 650 |
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|a Artificial intelligence.
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| 650 |
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|a Computer graphics.
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| 650 |
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|a Neural networks (Computer science).
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|a Physics.
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|a Computational intelligence.
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|a Engineering.
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|a Computational Intelligence.
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|a Theoretical, Mathematical and Computational Physics.
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|a Mathematical Models of Cognitive Processes and Neural Networks.
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| 650 |
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|a Artificial Intelligence (incl. Robotics).
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| 650 |
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|a Computer Imaging, Vision, Pattern Recognition and Graphics.
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| 710 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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| 776 |
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|i Printed edition:
|z 9789812878694
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| 830 |
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|a Cognitive Science and Technology,
|x 2195-3988
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| 856 |
4 |
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|u http://dx.doi.org/10.1007/978-981-287-871-7
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
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