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BioInformation Processing A Primer on Computational Cognitive Science /

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Peterson, James K. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Singapore : Springer Nature Singapore : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:Cognitive Science and Technology,
Temas:
Acceso en línea:Texto Completo

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300 |a XXXV, 570 p. 165 illus. in color.  |b online resource. 
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490 1 |a Cognitive Science and Technology,  |x 2195-3996 
505 0 |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. 
520 |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. 
650 0 |a Computational intelligence. 
650 0 |a Mathematical physics. 
650 0 |a Neural networks (Computer science) . 
650 0 |a Artificial intelligence. 
650 0 |a Image processing-Digital techniques. 
650 0 |a Computer vision. 
650 1 4 |a Computational Intelligence. 
650 2 4 |a Theoretical, Mathematical and Computational Physics. 
650 2 4 |a Mathematical Models of Cognitive Processes and Neural Networks. 
650 2 4 |a Artificial Intelligence. 
650 2 4 |a Computer Imaging, Vision, Pattern Recognition and Graphics. 
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