Methods for recognizing multispectral images based on neural networks - Peleshchak, Roman;Peleshchak, Ivan;Vysotska, Victoria
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This monograph presents the basic concepts, methods, and models of multispectral image recognition based on oscillatory and diagonalized neural networks in a logical sequence. In addition, the monograph contains sections on the modified Hecht-Nielsen theorem, optimizing the size of a neural network taking into account the nonlinear generalized error of the neural network model, creating a pseudo-spin neural network with reduced learning time, and creating a decision support model based on a diagonalized neural network.

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Produktbeschreibung
This monograph presents the basic concepts, methods, and models of multispectral image recognition based on oscillatory and diagonalized neural networks in a logical sequence. In addition, the monograph contains sections on the modified Hecht-Nielsen theorem, optimizing the size of a neural network taking into account the nonlinear generalized error of the neural network model, creating a pseudo-spin neural network with reduced learning time, and creating a decision support model based on a diagonalized neural network.
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Autorenporträt
Roman Peleshchak Professor and Doctor of Physical and Mathematical Sciences. E-mail: rpele@ukr.netIvan Peleshchak is Postgraduate. E-mail: peleshchakivan@gmail.com.Victoria Vysotska, PhD, Associate Professor and Deputy Head of Information Systems and Networks Department. Lviv Polytechnic National University, Lviv, Ukraine.