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  3. Neuronal Networks

Artificial Neuronal Networks: Application to Ecology and Evolution

Posted By: AvaxGenius
Date: 28 Sep 2023 14:27:02
Artificial Neuronal Networks: Application to Ecology and Evolution

Artificial Neuronal Networks: Application to Ecology and Evolution by Sovan Lek, Jean-François Guégan
English | PDF | 2000 | 275 Pages | ISBN : 3540669213 | 26.4 MB

In this book, an easily understandable account of modelling methods with artificial neuronal networks for practical applications in ecology and evolution is provided. Special features include examples of applications using both supervised and unsupervised training, comparative analysis of artificial neural networks and conventional statistical methods, and proposals to deal with poor datasets. Extensive references and a large range of topics make this book a useful guide for ecologists, evolutionary ecologists and population geneticists.
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Les fondements des réseaux de neurones

Posted By: IrGens
Date: 22 Nov 2022 19:29:55
Les fondements des réseaux de neurones

Les fondements des réseaux de neurones
.MP4, AVC, 1280x720, 30 fps | Français, AAC, 2 Ch | 2h 7m | 694 MB
Instructor: Madjid Khichane
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Wavelets in Neuroscience (Repost)

Posted By: AvaxGenius
Date: 6 Nov 2022 23:36:19
Wavelets in Neuroscience (Repost)

Wavelets in Neuroscience by Alexander E. Hramov, Alexey A. Koronovskii, Valeri A. Makarov, Alexey N. Pavlov, Evgenia Sitnikova
English | PDF(True) | 2015 | 331 Pages | ISBN : 3662438496 | 13.24 MB

This book examines theoretical and applied aspects of wavelet analysis in neurophysics, describing in detail different practical applications of the wavelet theory in the areas of neurodynamics and neurophysiology and providing a review of fundamental work that has been carried out in these fields over the last decade.
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Wavelets in Neuroscience

Posted By: AvaxGenius
Date: 23 Mar 2022 00:48:28
Wavelets in Neuroscience

Wavelets in Neuroscience by Alexander E. Hramov
English | PDF | 2021 | 397 Pages | ISBN : 3030759911 | 13.2 MB

This book illustrates how modern mathematical wavelet transform techniques offer fresh insights into the complex behavior of neural systems at different levels: from the microscopic dynamics of individual cells to the macroscopic behavior of large neural networks. It also demonstrates how and where wavelet-based mathematical tools can provide an advantage over classical approaches used in neuroscience. The authors well describe single neuron and populational neural recordings.
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