Richard meyes (38 risultati)

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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Master's Thesis from the year 2012 in the subject Physics - Other, grade: 1,7, RWTH Aachen University (1. Physikalisches Institut (IA)), language: English, abstract: In the history of computing hardware,Moore's law, named after Intel co-founder Gordon E.Moore, describes a long-termtrend, whereby the number of transistors that can be placedinexpensively on an integrated circuit doubles approximately every two years. Becausethe number of transistors is crucial for computing performance, significant performancegains could be achieved simply through complementary metal-oxide-semiconductor (CMOS)transistor downscaling. AlthoughMoore's law, which was mentioned for the first time in 1965,turned out to persist for almost five decades, the nano era poses significant problems to theconcept of downscaling. Upon approaching the size of atoms, quantum effects, such asquantum tunneling, pose fundamental barriers to the trend. Furthermore, the conventionalcomputing paradigm based on the Von-Neumann architecture and binary logic becomesincreasingly inefficient considering the growing complexity of todays computational tasks.Hence, new computational paradigms and alternative information processing architecturesmust be explored to extend the capabilities of future information technology beyond digitallogic. A fantastic example for such an alternative information processing architecture is thehuman brain. The brain provides superior computational features such as ultrahigh densityof processing units, low energy consumption per computational event, ultrahigh parallelismin computational execution, extremely flexible plasticity of connections between processingunits and fault-tolerant computing provided by a huge number of computational entities.Compared to today's programmable computers, biological systems are six to nine orders ofmagnitude more efficient in complex environments. For instance: simulating five secondsof brain activity takes IBM's state-of-the-art supercomputer Blue Gene a hundred times aslong, i.e. 500 s, during which it consumes 1.4MWof power, whereas the power dissipation inthe human central nervous system is of the order of 10W. Thus, it is not only extremelyinteresting but in terms of computational progress also highly desirable to understand how information is processed in the human brain. The conceptual idea developed within theframework of this thesis tries to contribute to this intention. [.]. …

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Paperback. Condizione: new. Paperback. Artificial intelligence (AI) is a concept, whose meaning and perception has changed considerably over the last decades. Starting off with individual and purely theoretical research efforts in the 1950s, AI has grown into a fully developed research field of modern times and may arguably emerge as one of the most important technological advancements of mankind. Despite these rapid technological advancements, some key questions revolving around the matter of transparency, interpretability and explainability of an AIs decision-making remain unanswered. Thus, a young research field coined with the general term Explainable AI (XAI) has emerged from increasingly strict requirements for AI to be used in safety critical or ethically sensitive domains. An important research branch of XAI is to develop methods that help to facilitate a deeper understanding for the learned knowledge of artificial neural systems. In this book, a series of scientific studies are presented that shed lighton how to adopt an empirical neuroscience inspired approach to investigate a neural networks learned representation in the same spirit as neuroscientific studies of the brain. Starting off with individual and purely theoretical research efforts in the 1950s, AI has grown into a fully developed research field of modern times and may arguably emerge as one of the most important technological advancements of mankind. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Taschenbuch. Condizione: Neu. Emulation of Bursting Neurons in Neuromorphic Hardware based on Phase-Change Materials | Richard Meyes | Taschenbuch | 124 S. | Englisch | 2015 | Anchor Academic Publishing | EAN 9783954893447 | Verantwortliche Person für die EU: Bedey & Thoms Media GmbH, Björn Bedey, Hermannstal 119k, 22119 Hamburg, info[at]diplom[dot]de | Anbieter: preigu. …

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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Artificial intelligence (AI) is a concept, whose meaning and perception has changed considerably over the last decades. Starting off with individual and purely theoretical research efforts in the 1950s, AI has grown into a fully developed research field of modern times and may arguably emerge as one of the most important technological advancements of mankind. Despite these rapid technological advancements, some key questions revolving around the matter of transparency, interpretability and explainability of an AI's decision-making remain unanswered. Thus, a young research field coined with the general term Explainable AI (XAI) has emerged from increasingly strict requirements for AI to be used in safety critical or ethically sensitive domains. An important research branch of XAI is to develop methods that help to facilitate a deeper understanding for the learned knowledge of artificial neural systems. In this book, a series of scientific studies are presented that shed lighton how to adopt an empirical neuroscience inspired approach to investigate a neural network's learned representation in the same spirit as neuroscientific studies of the brain.…

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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 124 pp. Englisch.

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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the history of computing hardware,Moores law, named after Intel co-founder Gordon E. Moore, describes a long-termtrend, whereby the number of transistors that can be placed inexpensively on an integrated circuit doubles approximately every two years [1]. Because the number of transistors is crucial for computing performance, significant performance gains could be achieved simply through complementary metal-oxide-semiconductor (CMOS) transistor downscaling. AlthoughMoores law, which was mentioned for the first time in 1965, turned out to persist for almost five decades, the nano era poses significant problems to the concept of downscaling [2]. Upon approaching the size of atoms, quantumeffects, such as quantum tunneling, pose fundamental barriers to the trend. Furthermore, the conventional computing paradigm based on the Von-Neumann architecture and binary logic becomes increasingly inefficient considering the growing complexity of todays computational tasks. Hence, new computational paradigms and alternative information processing architectures must be explored to extend the capabilities of future information technology beyond digital logic. A fantastic example for such an alternative information processing architecture is the human brain. The brain provides superior computational features such as ultrahigh density of processing units, low energy consumption per computational event, ultrahigh parallelism in computational execution, extremely flexible plasticity of connections between processing units and fault-tolerant computing provided by a huge number of computational entities. Compared to todays programmable computers, biological systems are six to nine orders of magnitude more efficient in complex environments [3]. For instance: simulating five seconds of brain activity takes IBMs state-of-the-art supercomputer Blue Gene a hundred times as long, i.e. 500 s, during which it consumes 1.4 MWof power, whereas the power dissipation in the human central nervous system is of the order of 10W[4, 5]. Thus, it is not only extremely interesting but in terms of computational progress also highly desirable to understand how information is processed in the human brain. The conceptual idea developed within the framework of this thesis tries to contribute to this intention. In contrast to most recent research dealing with the simulation and emulation of specific connections between nerve cells [5-12], the work of this thesis focuses on investigating, on [].…

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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Text Sample:Chapter 2 A Biological Background:The Human brain is vastly superior to the brain of other animals in its ability to exploit the physical environment in which the controlled organism has to operate. The remarkable complexity of the e.…

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