Author: Pier Luigi Gentili
Publisher: Frontiers Media SA
ISBN: 283255637X
Category : Science
Languages : en
Pages : 95
Book Description
Frontiers in Neuroscience, Neuromorphic Engineering is delighted to present the ‘Reviews and Perspectives in’ series of article collections. Reviews and Perspectives in Neuromorphic Engineering: Novel Neuromorphic Computing Approaches Research Topic will publish high-quality scholarly reviews and perspective papers on key topics in Neuromorphic Computing. It aims to highlight recent advances in neuromorphic computing in software, hardware, and wetware whilst emphasizing important directions, novel and unconventional approaches, and new possibilities for future inquiries. The research presented will promote discussion in the neuromorphic computing community that will translate to best practice applications. We welcome Review, Mini Review, Opinion, General Commentary, and Perspective articles on themes including, but not limited to: • Innovative architectures and models in neuromorphic computing • Oscillatory Neural Networks computing • Reservoir computing • Chemical computing • Protein computing • Synthetic cells • Analog computing • Bayesian inference and fuzzy logic • Linking neuromorphic and quantum computing • Novel materials for neuromorphic computing • Unconventional neuromorphic approaches • Photonic computing • 3D integrated Neural Network • Physical Chemistry of materials and systems for neuromorphic computing.
Reviews and Perspectives in Neuromorphic Engineering: Novel Neuromorphic Computing Approaches
Author: Pier Luigi Gentili
Publisher: Frontiers Media SA
ISBN: 283255637X
Category : Science
Languages : en
Pages : 95
Book Description
Frontiers in Neuroscience, Neuromorphic Engineering is delighted to present the ‘Reviews and Perspectives in’ series of article collections. Reviews and Perspectives in Neuromorphic Engineering: Novel Neuromorphic Computing Approaches Research Topic will publish high-quality scholarly reviews and perspective papers on key topics in Neuromorphic Computing. It aims to highlight recent advances in neuromorphic computing in software, hardware, and wetware whilst emphasizing important directions, novel and unconventional approaches, and new possibilities for future inquiries. The research presented will promote discussion in the neuromorphic computing community that will translate to best practice applications. We welcome Review, Mini Review, Opinion, General Commentary, and Perspective articles on themes including, but not limited to: • Innovative architectures and models in neuromorphic computing • Oscillatory Neural Networks computing • Reservoir computing • Chemical computing • Protein computing • Synthetic cells • Analog computing • Bayesian inference and fuzzy logic • Linking neuromorphic and quantum computing • Novel materials for neuromorphic computing • Unconventional neuromorphic approaches • Photonic computing • 3D integrated Neural Network • Physical Chemistry of materials and systems for neuromorphic computing.
Publisher: Frontiers Media SA
ISBN: 283255637X
Category : Science
Languages : en
Pages : 95
Book Description
Frontiers in Neuroscience, Neuromorphic Engineering is delighted to present the ‘Reviews and Perspectives in’ series of article collections. Reviews and Perspectives in Neuromorphic Engineering: Novel Neuromorphic Computing Approaches Research Topic will publish high-quality scholarly reviews and perspective papers on key topics in Neuromorphic Computing. It aims to highlight recent advances in neuromorphic computing in software, hardware, and wetware whilst emphasizing important directions, novel and unconventional approaches, and new possibilities for future inquiries. The research presented will promote discussion in the neuromorphic computing community that will translate to best practice applications. We welcome Review, Mini Review, Opinion, General Commentary, and Perspective articles on themes including, but not limited to: • Innovative architectures and models in neuromorphic computing • Oscillatory Neural Networks computing • Reservoir computing • Chemical computing • Protein computing • Synthetic cells • Analog computing • Bayesian inference and fuzzy logic • Linking neuromorphic and quantum computing • Novel materials for neuromorphic computing • Unconventional neuromorphic approaches • Photonic computing • 3D integrated Neural Network • Physical Chemistry of materials and systems for neuromorphic computing.
Neuromorphic Photonics
Author: Paul R. Prucnal
Publisher: CRC Press
ISBN: 1498725244
Category : Science
Languages : en
Pages : 412
Book Description
This book sets out to build bridges between the domains of photonic device physics and neural networks, providing a comprehensive overview of the emerging field of "neuromorphic photonics." It includes a thorough discussion of evolution of neuromorphic photonics from the advent of fiber-optic neurons to today’s state-of-the-art integrated laser neurons, which are a current focus of international research. Neuromorphic Photonics explores candidate interconnection architectures and devices for integrated neuromorphic networks, along with key functionality such as learning. It is written at a level accessible to graduate students, while also intending to serve as a comprehensive reference for experts in the field.
Publisher: CRC Press
ISBN: 1498725244
Category : Science
Languages : en
Pages : 412
Book Description
This book sets out to build bridges between the domains of photonic device physics and neural networks, providing a comprehensive overview of the emerging field of "neuromorphic photonics." It includes a thorough discussion of evolution of neuromorphic photonics from the advent of fiber-optic neurons to today’s state-of-the-art integrated laser neurons, which are a current focus of international research. Neuromorphic Photonics explores candidate interconnection architectures and devices for integrated neuromorphic networks, along with key functionality such as learning. It is written at a level accessible to graduate students, while also intending to serve as a comprehensive reference for experts in the field.
Neuromorphic Cognitive Systems
Author: Qiang Yu
Publisher: Springer
ISBN: 3319553100
Category : Technology & Engineering
Languages : en
Pages : 180
Book Description
This book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system network of neurons to perform spike-based information processing, computing, and high-level cognitive tasks. It is beneficial to a wide spectrum of readers, including undergraduate and postgraduate students and researchers who are interested in neuromorphic computing and neuromorphic engineering, as well as engineers and professionals in industry who are involved in the design and applications of neuromorphic cognitive systems, neuromorphic sensors and processors, and cognitive robotics. The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromorphic cognitive systems are urgently needed. The topics covered in this book range from the neuronal level to the system level. In the neuronal level, synaptic adaptation plays an important role in learning patterns. In order to perform higher-level cognitive functions such as recognition and memory, spiking neurons with learning abilities are consistently integrated, building a system with encoding, learning and memory functionalities. The book describes these aspects in detail.
Publisher: Springer
ISBN: 3319553100
Category : Technology & Engineering
Languages : en
Pages : 180
Book Description
This book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system network of neurons to perform spike-based information processing, computing, and high-level cognitive tasks. It is beneficial to a wide spectrum of readers, including undergraduate and postgraduate students and researchers who are interested in neuromorphic computing and neuromorphic engineering, as well as engineers and professionals in industry who are involved in the design and applications of neuromorphic cognitive systems, neuromorphic sensors and processors, and cognitive robotics. The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromorphic cognitive systems are urgently needed. The topics covered in this book range from the neuronal level to the system level. In the neuronal level, synaptic adaptation plays an important role in learning patterns. In order to perform higher-level cognitive functions such as recognition and memory, spiking neurons with learning abilities are consistently integrated, building a system with encoding, learning and memory functionalities. The book describes these aspects in detail.
Unconventional Computation From Digital to Brain-like Neuromorphic
Author: Mahyar Shahsavari
Publisher:
ISBN: 9783330865792
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN: 9783330865792
Category :
Languages : en
Pages :
Book Description
The Making of a Neuromorphic Visual System
Author: Christoph Rasche
Publisher: Springer Science & Business Media
ISBN: 0387234691
Category : Medical
Languages : en
Pages : 142
Book Description
The reader is presented an approach to the construction of a visual system, which is behaviorally, computationally and neurally motivated. The central goal is to characterize the process of visual categorization and to find a suitable representation format that can successfully deal with the structural variability existent within visual categories. It does not define such representations a priori but attempts to show directions on how to gradually work towards them. The book reviews past and existent theories of visual object and shape recognition in the fields of computer vision, neuroscience and psychology. The entire range of computations is discussed, as for example contour extraction in retinal circuits, orientation determination in cortical networks, position and scale independence of shape, as well as the issue of object and shape representation in a neural substrate. Region-based approaches are discussed and are modeled with wave-propagating networks. It is demonstrated how those networks operate on gray-scale images. A completely novel shape recognition architecture is proposed that can recognize simple shapes under various degraded conditions. It is discussed how such networks can be used for constructing basic-level object representations. It is envisioned how those networks can be implemented using the method of neuromorphic engineering, an analog electronic hardware substrate than can run neural computations in real-time and with little power.
Publisher: Springer Science & Business Media
ISBN: 0387234691
Category : Medical
Languages : en
Pages : 142
Book Description
The reader is presented an approach to the construction of a visual system, which is behaviorally, computationally and neurally motivated. The central goal is to characterize the process of visual categorization and to find a suitable representation format that can successfully deal with the structural variability existent within visual categories. It does not define such representations a priori but attempts to show directions on how to gradually work towards them. The book reviews past and existent theories of visual object and shape recognition in the fields of computer vision, neuroscience and psychology. The entire range of computations is discussed, as for example contour extraction in retinal circuits, orientation determination in cortical networks, position and scale independence of shape, as well as the issue of object and shape representation in a neural substrate. Region-based approaches are discussed and are modeled with wave-propagating networks. It is demonstrated how those networks operate on gray-scale images. A completely novel shape recognition architecture is proposed that can recognize simple shapes under various degraded conditions. It is discussed how such networks can be used for constructing basic-level object representations. It is envisioned how those networks can be implemented using the method of neuromorphic engineering, an analog electronic hardware substrate than can run neural computations in real-time and with little power.
Oxide Spintronics
Author: Tamalika Banerjee
Publisher: CRC Press
ISBN: 0429886896
Category : Science
Languages : en
Pages : 207
Book Description
Oxide materials have been used in mainstream semiconductor technology for several decades and have served as important components, such as gate insulators or capacitors, in integrated circuits. However, in recent decades, this material class has emerged in its own right as a potential contender for alternative technologies, generally designated as ‘beyond Moore’. The 2004 discovery by Ohtomo and Hwang was a global trendsetter in this context. It involved observing a two-dimensional, high-mobility electron gas at the heterointerface between two insulating oxides, LaAlO3 and SrTiO3, supported by the rise of nascent deposition and growth-monitoring techniques, which was an important direction in materials science research. The quest to understand the origin of this unparalleled physical property and to find other emergent properties has been an active field of research in condensed matter that has united researchers with expertise in diverse fields such as thin-film growth, defect control, advanced microscopy, semiconductor technology, computation, magnetism and electricity, spintronics, nanoscience, and nanotechnology.
Publisher: CRC Press
ISBN: 0429886896
Category : Science
Languages : en
Pages : 207
Book Description
Oxide materials have been used in mainstream semiconductor technology for several decades and have served as important components, such as gate insulators or capacitors, in integrated circuits. However, in recent decades, this material class has emerged in its own right as a potential contender for alternative technologies, generally designated as ‘beyond Moore’. The 2004 discovery by Ohtomo and Hwang was a global trendsetter in this context. It involved observing a two-dimensional, high-mobility electron gas at the heterointerface between two insulating oxides, LaAlO3 and SrTiO3, supported by the rise of nascent deposition and growth-monitoring techniques, which was an important direction in materials science research. The quest to understand the origin of this unparalleled physical property and to find other emergent properties has been an active field of research in condensed matter that has united researchers with expertise in diverse fields such as thin-film growth, defect control, advanced microscopy, semiconductor technology, computation, magnetism and electricity, spintronics, nanoscience, and nanotechnology.
Memristors for Neuromorphic Circuits and Artificial Intelligence Applications
Author: Jordi Suñé
Publisher: MDPI
ISBN: 3039285769
Category : Technology & Engineering
Languages : en
Pages : 244
Book Description
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.
Publisher: MDPI
ISBN: 3039285769
Category : Technology & Engineering
Languages : en
Pages : 244
Book Description
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.
Neural Engineering
Author: Chris Eliasmith
Publisher: MIT Press
ISBN: 9780262550604
Category : Computers
Languages : en
Pages : 384
Book Description
A synthesis of current approaches to adapting engineering tools to the study of neurobiological systems.
Publisher: MIT Press
ISBN: 9780262550604
Category : Computers
Languages : en
Pages : 384
Book Description
A synthesis of current approaches to adapting engineering tools to the study of neurobiological systems.
Calculus of Thought
Author: Daniel M Rice
Publisher: Academic Press
ISBN: 0124104525
Category : Mathematics
Languages : en
Pages : 295
Book Description
Calculus of Thought: Neuromorphic Logistic Regression in Cognitive Machines is a must-read for all scientists about a very simple computation method designed to simulate big-data neural processing. This book is inspired by the Calculus Ratiocinator idea of Gottfried Leibniz, which is that machine computation should be developed to simulate human cognitive processes, thus avoiding problematic subjective bias in analytic solutions to practical and scientific problems. The reduced error logistic regression (RELR) method is proposed as such a "Calculus of Thought." This book reviews how RELR's completely automated processing may parallel important aspects of explicit and implicit learning in neural processes. It emphasizes the fact that RELR is really just a simple adjustment to already widely used logistic regression, along with RELR's new applications that go well beyond standard logistic regression in prediction and explanation. Readers will learn how RELR solves some of the most basic problems in today's big and small data related to high dimensionality, multi-colinearity, and cognitive bias in capricious outcomes commonly involving human behavior. - Provides a high-level introduction and detailed reviews of the neural, statistical and machine learning knowledge base as a foundation for a new era of smarter machines - Argues that smarter machine learning to handle both explanation and prediction without cognitive bias must have a foundation in cognitive neuroscience and must embody similar explicit and implicit learning principles that occur in the brain
Publisher: Academic Press
ISBN: 0124104525
Category : Mathematics
Languages : en
Pages : 295
Book Description
Calculus of Thought: Neuromorphic Logistic Regression in Cognitive Machines is a must-read for all scientists about a very simple computation method designed to simulate big-data neural processing. This book is inspired by the Calculus Ratiocinator idea of Gottfried Leibniz, which is that machine computation should be developed to simulate human cognitive processes, thus avoiding problematic subjective bias in analytic solutions to practical and scientific problems. The reduced error logistic regression (RELR) method is proposed as such a "Calculus of Thought." This book reviews how RELR's completely automated processing may parallel important aspects of explicit and implicit learning in neural processes. It emphasizes the fact that RELR is really just a simple adjustment to already widely used logistic regression, along with RELR's new applications that go well beyond standard logistic regression in prediction and explanation. Readers will learn how RELR solves some of the most basic problems in today's big and small data related to high dimensionality, multi-colinearity, and cognitive bias in capricious outcomes commonly involving human behavior. - Provides a high-level introduction and detailed reviews of the neural, statistical and machine learning knowledge base as a foundation for a new era of smarter machines - Argues that smarter machine learning to handle both explanation and prediction without cognitive bias must have a foundation in cognitive neuroscience and must embody similar explicit and implicit learning principles that occur in the brain
Artificial Intelligence By Example
Author: Denis Rothman
Publisher: Packt Publishing Ltd
ISBN: 1839212810
Category : Computers
Languages : en
Pages : 579
Book Description
Understand the fundamentals and develop your own AI solutions in this updated edition packed with many new examples Key FeaturesAI-based examples to guide you in designing and implementing machine intelligenceBuild machine intelligence from scratch using artificial intelligence examplesDevelop machine intelligence from scratch using real artificial intelligenceBook Description AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions. What you will learnApply k-nearest neighbors (KNN) to language translations and explore the opportunities in Google TranslateUnderstand chained algorithms combining unsupervised learning with decision treesSolve the XOR problem with feedforward neural networks (FNN) and build its architecture to represent a data flow graphLearn about meta learning models with hybrid neural networksCreate a chatbot and optimize its emotional intelligence deficiencies with tools such as Small Talk and data loggingBuilding conversational user interfaces (CUI) for chatbotsWriting genetic algorithms that optimize deep learning neural networksBuild quantum computing circuitsWho this book is for Developers and those interested in AI, who want to understand the fundamentals of Artificial Intelligence and implement them practically. Prior experience with Python programming and statistical knowledge is essential to make the most out of this book.
Publisher: Packt Publishing Ltd
ISBN: 1839212810
Category : Computers
Languages : en
Pages : 579
Book Description
Understand the fundamentals and develop your own AI solutions in this updated edition packed with many new examples Key FeaturesAI-based examples to guide you in designing and implementing machine intelligenceBuild machine intelligence from scratch using artificial intelligence examplesDevelop machine intelligence from scratch using real artificial intelligenceBook Description AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions. What you will learnApply k-nearest neighbors (KNN) to language translations and explore the opportunities in Google TranslateUnderstand chained algorithms combining unsupervised learning with decision treesSolve the XOR problem with feedforward neural networks (FNN) and build its architecture to represent a data flow graphLearn about meta learning models with hybrid neural networksCreate a chatbot and optimize its emotional intelligence deficiencies with tools such as Small Talk and data loggingBuilding conversational user interfaces (CUI) for chatbotsWriting genetic algorithms that optimize deep learning neural networksBuild quantum computing circuitsWho this book is for Developers and those interested in AI, who want to understand the fundamentals of Artificial Intelligence and implement them practically. Prior experience with Python programming and statistical knowledge is essential to make the most out of this book.