Search Results: 'neural network system'

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24 results for "neural network system"
Online Learning of a Neural Fuel Control System for Gaseous Fueled SI Engines By Travis Wiens
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This PhD dissertation presents a new type of fuel control algorithm for gaseous fuelled vehicles. Gaseous fuels such as hydrogen and natural gas have been shown to be less polluting than liquid... More > fuels, both at the tailpipe and on a total cycle. Unfortunately, it can be expensive to convert vehicles to gaseous fuels. One of major development costs for a new vehicle is the development and calibration of the fuel controller. The research presented here includes a fuel controller which does not require an expensive calibration phase. The controller is based upon a two-part model, using online training of a neural network to model the engine’s steady state characteristics. An experimental test was performed, in which the controller was installed on a truck fuelled by natural gas. The tailpipe emissions of the truck with the new controller showed better results than the OEM controller on both carbon monoxide and nitrogen oxides, and required no calibration and very little information about the engine.< Less
Online Learning of a Neural Fuel Control System for Gaseous Fueled SI Engines By Travis Wiens
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This PhD dissertation presents a new type of fuel control algorithm for gaseous fuelled vehicles. Gaseous fuels such as hydrogen and natural gas have been shown to be less polluting than liquid... More > fuels, both at the tailpipe and on a total cycle. Unfortunately, it can be expensive to convert vehicles to gaseous fuels. One of major development costs for a new vehicle is the development and calibration of the fuel controller. The research presented here includes a fuel controller which does not require an expensive calibration phase. The controller is based upon a two-part model, using online training of a neural network to model the engine’s steady state characteristics. An experimental test was performed, in which the controller was installed on a truck fuelled by natural gas. The tailpipe emissions of the truck with the new controller showed better results than the OEM controller on both carbon monoxide and nitrogen oxides, and required no calibration and very little information about the engine.< Less
Thinking Networks - the Large and Small of it By Kieran Greer
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Ships in 3-5 business days.
It is clear today how much people are dependent on digital information sources. As this dependency grows then so will the demand for a higher quality of information, where we are now moving into a... More > service-based environment. This book describes different aspects of such an environment and is both important and timely for future Internet-based or mobile information networks. It considers specifically how intelligence can be added to these networks and what added benefits the intelligence might bring. For example, can a network intelligently optimise the services that it provides, or work out how to solve a more difficult task for a user? This book is mainly a research monograph, but also contains blue sky research and informative or teaching sections. The second half of the book discusses some research ideas that propose different levels of reasoning that can be performed over an information network and would be of interest to both academic or industrial researchers looking to build these intelligent systems.< Less
Thinking Networks - the Large and Small of it (eBook) By Kieran Greer
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It is clear today how much people are dependent on digital information sources. As this dependency grows then so will the demand for a higher quality of information, where we are now moving into a... More > service-based environment. This book describes different aspects of such an environment and is both important and timely for future Internet-based or mobile information networks. It considers specifically how intelligence can be added to these networks and what added benefits the intelligence might bring. For example, can a network intelligently optimise the services that it provides, or work out how to solve a more difficult task for a user? This book is mainly a research monograph, but also contains blue sky research and informative or teaching sections. The second half of the book discusses some research ideas that propose different levels of reasoning that can be performed over an information network and would be of interest to both academic or industrial researchers looking to build these intelligent systems.< Less
Modelling of Deterministic, Fuzzy and Probablistic Dynamical Systems: M.S. Thesis By Rohitash Chandra
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Recurrent neural networks and hidden Markov models have been the popular tools for sequence recognition problems such as automatic speech recognition. This work investigates the combination of... More > recurrent neural networks and hidden Markov models into the hybrid architecture. This combination is feasible due to the similarity of the architectural dynamics of the two systems. Initial experiments were done by training recurrent neural networks to behave like finite-state automata using genetic algorithms in order to demonstrate that their structure is sufficiently rich to represent dynamical systems. The results show that hybrid recurrent neural networks can learn and represent dynamical systems such as finite automaton. Finally, the proposed hybrid architecture is applied to automatic speech phoneme recognition. The results show that hybrid recurrent neural networks perform with some conditions and degree of success when applied to difficult real-world problems.< Less
Modelling of Deterministic, Fuzzy and Probablistic Dynamical Systems: M.S. Thesis By Rohitash Chandra
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Recurrent neural networks and hidden Markov models have been the popular tools for sequence recognition problems such as automatic speech recognition. This work investigates the combination of... More > recurrent neural networks and hidden Markov models into the hybrid architecture. This combination is feasible due to the similarity of the architectural dynamics of the two systems. Initial experiments were done by training recurrent neural networks to behave like finite-state automata using genetic algorithms in order to demonstrate that their structure is sufficiently rich to represent dynamical systems. The results show that hybrid recurrent neural networks can learn and represent dynamical systems such as finite automaton. Finally, the proposed hybrid architecture is applied to automatic speech phoneme recognition. The results show that hybrid recurrent neural networks perform with some conditions and degree of success when applied to difficult real-world problems.< Less
RoboSight User Manual V1.0 By Robin Knight, Dave Hygh
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RoboSight by RNIS offers an affordable, but powerful vision recognition system, ideal for robotic platforms and small embedded applications. Powered by the CogniMem CM-1K neural network chip... More > developed by General Vision, complex visual objects are readily detected and categorized from patterns previously trained by the user or the embedding system. The recognized visual categories can then be fed to the higher-level functions of the controlling system to guide goal decisions, object localization, platform movement and navigation, and environment manipulation.< Less
Practical Artificial Intelligence Programming With Java By Mark Watson
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This book uses both best of breed open source software and the author's own libraries to introduce the reader to Artificial Intelligence (AI) technologies like genetic algorithms, neural networks,... More > expert systems, machine learning, and statistical natural language processing (NLP).< Less
Practical Artificial Intelligence Programming With Java By Mark Watson
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This book uses both best of breed open source software and the author's own libraries to introduce the reader to Artificial Intelligence (AI) technologies like genetic algorithms, neural networks,... More > expert systems, machine learning, and statistical natural language processing (NLP).< Less
The Neuroanalyst By Avi Peled
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The taxonomy of the DSM is not brain-related and thus disconnects clinical psychiatry from its etiopathological neuroscientific origins. This manual re-conceptualizes mental disorders as brain... More > disorders by introducing insights from computational neuroscience, a discipline in a position to explain brain disorganization and thus offers a valid methodical foundation for understanding mental disorders.< Less