£114.66

Springer Models of Neurons and Perceptrons - Vol 770

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Description

Explore the mathematical foundations of neural structures with Models of Neurons and Perceptrons: Selected Problems and Challenges. Part of the Studies in Computational Intelligence series (Volume 770), this book provides a deep look into both biological foundations and artificial neural networks. Readers can examine the relationship between mathematical models and the electronic circuits used to represent neurons and synapses. The text offers a detailed analysis of how these circuits function in relation to their mathematical counterparts. Beyond basic concepts, the book addresses advanced topics such as the topological conjugacy of dynamical systems and shadowing. This resource is designed for those looking to understand the complex connection between biological processes, mathematical theory, and electronic modeling in the field of AI and machine learning.

Key Features

Covers mathematical models of neurons and multilayer neural structures for a deep technical understanding.

Analyzes electronic circuits used as models for both the neuron and the synapse.

Provides a comprehensive overview of biological foundations and artificial neural networks.

Examines the direct relationship between electronic circuits and mathematical models.

Includes advanced mathematical topics like topological conjugacy of dynamical systems.

Part of the Springer Studies in Computational Intelligence series, volume 770.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
28 May 2018
Listed Since
16 March 2018

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