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Filtering by: Creator Ek, M. Remove constraint Creator: Ek, M. Degree Field Electrical and Computer Engineering Remove constraint Degree Field: Electrical and Computer Engineering Subject Neural networks (Computer science) Remove constraint Subject: Neural networks (Computer science)

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  • Analysis and synthesis of neural networks

    Creator:
    Skelton, Jeanette K.
    Abstract:
    The brain has long attracted the interest of researchers. Some tasks, such as pattern recognition and optimization, have proven to be exceptionally difficult for conventional computing systems to perform, but are executed by the brain almost effortlessly. Due to the large number of neurons and interconnections, it has proven impossible...
    Resource Type:
    Masters Thesis
    Full Text:
    : Redacted for Privacy John M. ay The brain has long attracted the interest of researchers. Some tasks, such

  • Nonlinear neural control with power systems applications

    Creator:
    Chen, Dingguo
    Abstract:
    Extensive studies have been undertaken on the transient stability of large interconnected power systems with flexible ac transmission systems (FACTS) devices installed. Varieties of control methodologies have been proposed to stabilize the postfault system which would otherwise eventually lose stability without a proper control. Generally speaking, regular transient stability is...
    Resource Type:
    Dissertation
    Full Text:
    current M system inertia P real (or active) power Q reactive power s series TCSC compensation degree t

  • Neural network control of nonlinear discrete time systems

    Creator:
    Zakrzewski, Radoslaw Romuald
    Abstract:
    The main focus of this work is on the problem of existence of nonlinear optimal controllers realizable by artificial neural networks. Theoretical justification, currently available for control applications of neural networks, is rather limited. For example, it is unclear which neural architectures are capable of performing which control tasks. This...
    Resource Type:
    Dissertation
    Full Text:
    collection of M neurons, gi, i = 1, . . . , M, each with the same activation function and with the same