Memristors for Neuromorphic Circuits and Artificial Intelligence Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Memristors for Neuromorphic Circuits and Artificial Intelligence Applications write by Jordi Suñé. This book was released on 2020-04-09. Memristors for Neuromorphic Circuits and Artificial Intelligence Applications available in PDF, EPUB and Kindle. Artificial Intelligence (AI) has found many applications in the past decade due to the ever increasing computing power. Artificial Neural Networks are inspired in the brain structure and consist in the interconnection of artificial neurons through artificial synapses. Training these systems requires huge amounts of data and, after the network is trained, it can recognize unforeseen data and provide useful information. The so-called Spiking Neural Networks behave similarly to how the brain functions and are very energy efficient. Up to this moment, both spiking and conventional neural networks have been implemented in software programs running on conventional computing units. However, this approach requires high computing power, a large physical space and is energy inefficient. Thus, there is an increasing interest in developing AI tools directly implemented in hardware. The first hardware demonstrations have been based on CMOS circuits for neurons and specific communication protocols for synapses. However, to further increase training speed and energy efficiency while decreasing system size, the combination of CMOS neurons with memristor synapses is being explored. The memristor is a resistor with memory which behaves similarly to biological synapses. This book explores the state-of-the-art of neuromorphic circuits implementing neural networks with memristors for AI applications.
Memristors for Neuromorphic Circuits and Artificial Intelligence Applications
Memristors for Neuromorphic Circuits and Artificial Intelligence Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Memristors for Neuromorphic Circuits and Artificial Intelligence Applications write by Jordi Suñé. This book was released on 2020. Memristors for Neuromorphic Circuits and Artificial Intelligence Applications available in PDF, EPUB and Kindle. Artificial Intelligence (AI) has found many applications in the past decade due to the ever increasing computing power. Artificial Neural Networks are inspired in the brain structure and consist in the interconnection of artificial neurons through artificial synapses. Training these systems requires huge amounts of data and, after the network is trained, it can recognize unforeseen data and provide useful information. The so-called Spiking Neural Networks behave similarly to how the brain functions and are very energy efficient. Up to this moment, both spiking and conventional neural networks have been implemented in software programs running on conventional computing units. However, this approach requires high computing power, a large physical space and is energy inefficient. Thus, there is an increasing interest in developing AI tools directly implemented in hardware. The first hardware demonstrations have been based on CMOS circuits for neurons and specific communication protocols for synapses. However, to further increase training speed and energy efficiency while decreasing system size, the combination of CMOS neurons with memristor synapses is being explored. The memristor is a resistor with memory which behaves similarly to biological synapses. This book explores the state-of-the-art of neuromorphic circuits implementing neural networks with memristors for AI applications.
Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications
Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications write by Christos Volos. This book was released on 2021-06-17. Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications available in PDF, EPUB and Kindle. 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. 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. Covers a broad range of interdisciplinary topics between mathematics, circuits, realizations, and practical applications related to nonlinear dynamical systems, nanotechnology, analog and digital systems, computer science and artificial intelligence Presents recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) Includes interesting applications of mem-elements in nonlinear dynamical systems, analog and digital systems, neuromorphic circuits, computer science and artificial intelligence
Memristor
Memristor - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Memristor write by Yao-Feng Chang. This book was released on 2021-11-17. Memristor available in PDF, EPUB and Kindle. This book provides a platform for interdisciplinary research into unconventional computing with emerging physical substrates. With a focus on memristor devices, the chapter authors discuss a wide range of topics, including memristor theory, mathematical modelling, circuit theory, memristor-mate, memristor security, artificial intelligence, and much more.
Advanced Memristor Modeling
Advanced Memristor Modeling - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advanced Memristor Modeling write by Valeri Mladenov. This book was released on 2019-02-19. Advanced Memristor Modeling available in PDF, EPUB and Kindle. The investigation of new memory schemes, neural networks, computer systems and many other improved electronic devices is very important for future generation's electronic circuits and for their widespread application in all the areas of industry. In this aspect the analysis of new efficient and advanced electronic elements and circuits is an essential field of the highly developed electrical and electronic engineering. The resistance-switching phenomenon, observed in many amorphous oxides has been investigated since 1970 and it is a promising technology for constructing new electronic memories. It has been established that such oxide materials have the ability for changing their conductance in accordance to the applied voltage and memorizing their state for a long-time interval. Similar behaviour has been predicted for the memristor element by Leon Chua in 1971. The memristor is proposed in accordance to symmetry considerations and the relationships between the four basic electric quantities - electric current i, voltage v, charge q and magnetic flux Ψ. The memristor is an essential passive one-port element together with the resistor, inductor, and capacitor. The Williams HP research group has made a link between resistive switching devices, and the memristor proposed by Chua. A number of scientific papers related to memristors and memristor devices have been issued and several memristor models have been proposed. The memristor is a highly nonlinear component. It relates the electric charge q and the flux linkage, expressed as a time integral of the voltage. The memristor element has the important capability for remembering the electric charge passed through its cross-section and its respective resistance, when the electrical signals are switched off. Due to its nano-scale dimensions, non-volatility and memorizing properties, the memristor is a sound potential candidate for application in computer high-density memories, artificial neural networks and in many other electronic devices.
