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Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications
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Mem-elements for Neuromorphic Circuits with Artificial Intelligence ApplicationsНазвание: Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications
Автор: Christos Volos, Viet-Thanh Pham
Издательство: Academic Press, Elsevier
Год: 2021
Страниц: 570
Язык: английский
Формат: pdf (true)
Размер: 43.1 MB

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling.

The memristor definition is based solely on the fundamental circuit variables of current and voltage and their time-integrals, just like the resistor, capacitor, and inductor. Unlike those three elements, however, which are allowed in linear time-invariant system theory, memristors of interest have a dynamic function with memory and may be described as some function of net charge. There is no such thing as a standard memristor. Instead, each device implements a particular function, wherein the integral of voltage determines the integral of current, and vice versa. A linear time-invariant memristor, with a constant value for memristance, is simply a conventional resistor. Manufactured devices are never purely memristors (ideal memristor), but also exhibit some capacitance and resistance.

As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields.

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