BioInformation Processing [electronic resource] : A Primer on Computational Cognitive  Science /
Peterson, James K.author.
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.
Description based upon print version of record.
Includes bibliographical references and index.
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.
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.
Computational intelligence.
Mathematical physics.
Neural networks (Computer science) .
Artificial intelligence.
Optical data processing.
Computational Intelligence.
Theoretical, Mathematical and Computational Physics.
Mathematical Models of Cognitive Processes and Neural Networks.
Artificial Intelligence.
Computer Imaging, Vision, Pattern Recognition and Graphics.