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Computational neuroscience = an esse...
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Mallot, Hanspeter A.
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Computational neuroscience = an essential guide to membrane potentials, receptive fields, and neural networks /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Computational neuroscience/ by Hanspeter A. Mallot.
其他題名:
an essential guide to membrane potentials, receptive fields, and neural networks /
作者:
Mallot, Hanspeter A.
出版者:
Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:
xiii, 280 p. :ill. (some col.), digital ;24 cm.
內容註:
Chapter 1. Excitable Membranes and Neural Conduction -- Chapter 2. Receptive Fields and the Specificity of Neuronal Firing -- Chapter 3. Functional Models of Receptive Fields -- Chapter 4. Fourier Analysis for Neuroscientists -- Chapter 5. Artificial Neural Networks and Classification -- Chapter 6. Artificial Neural Networks With Interacting Output Units -- Chapter 7. Coding and Representation.
Contained By:
Springer Nature eBook
標題:
Computational neuroscience. -
電子資源:
https://doi.org/10.1007/978-3-031-75705-1
ISBN:
9783031757051
Computational neuroscience = an essential guide to membrane potentials, receptive fields, and neural networks /
Mallot, Hanspeter A.
Computational neuroscience
an essential guide to membrane potentials, receptive fields, and neural networks /[electronic resource] :by Hanspeter A. Mallot. - Second edition. - Cham :Springer Nature Switzerland :2024. - xiii, 280 p. :ill. (some col.), digital ;24 cm.
Chapter 1. Excitable Membranes and Neural Conduction -- Chapter 2. Receptive Fields and the Specificity of Neuronal Firing -- Chapter 3. Functional Models of Receptive Fields -- Chapter 4. Fourier Analysis for Neuroscientists -- Chapter 5. Artificial Neural Networks and Classification -- Chapter 6. Artificial Neural Networks With Interacting Output Units -- Chapter 7. Coding and Representation.
This book provides an essential introduction to modeling the nervous system at various levels. Readers will learn about the intricate mechanisms of neural activity, receptive fields, neural networks, and information coding. The chapters cover topics such as membrane potentials, the Hodgkin-Huxley theory, receptive fields and their specificity for important stimulus dimensions, Fourier analysis for neuroscientists, pattern recognition and self-organization in neural networks, and the structure of neural representations. The second edition includes revised text and figures for improved readability and completeness. Key points are highlighted throughout to help readers keep track of central ideas. Researchers in the field of neuroscience with backgrounds in biology, psychology, or medicine will find this book particularly beneficial. It is also an invaluable reference for all neuroscientists who use computational methods in their daily work. Whether you are a theoretical scientist approaching the field or an experienced practitioner seeking to deepen your understanding, "Computational Neuroscience - An Essential Guide to Membrane Potentials, Receptive Fields, and Neural Networks" offers a comprehensive guide to mastering the fundamentals of this dynamic discipline.
ISBN: 9783031757051
Standard No.: 10.1007/978-3-031-75705-1doiSubjects--Topical Terms:
610819
Computational neuroscience.
LC Class. No.: QP357.5
Dewey Class. No.: 612.80285
Computational neuroscience = an essential guide to membrane potentials, receptive fields, and neural networks /
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Chapter 1. Excitable Membranes and Neural Conduction -- Chapter 2. Receptive Fields and the Specificity of Neuronal Firing -- Chapter 3. Functional Models of Receptive Fields -- Chapter 4. Fourier Analysis for Neuroscientists -- Chapter 5. Artificial Neural Networks and Classification -- Chapter 6. Artificial Neural Networks With Interacting Output Units -- Chapter 7. Coding and Representation.
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