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Showing 1 to 4 of 4 for “"network adaptation"”.

  1. Adaptive function modal learning neural networks

    Modal learning method is a neural network learning term that refers to a single neural network which combines with more than one mode of learning. It aims to achieve more powerful learning results than a neural network combines with only one single mode of learning. This thesis introduces a novel …

    london-metro Repository record for Adaptive function modal learning neural networks (opens in a new tab)

  2. Enabling Network Stability in a Scalable Software-Defined Data Center Network

    In the recent past, Data Centre Network (DCN) has received a lot of research attention because of the indispensable role that DCNs play in modern-day network communication as; the data storage container for on-demand service provisioning. One of the major responsibilities of the DCN is the …

    zulu Repository record for Enabling Network Stability in a Scalable Software-Defined Data Center Network (opens in a new tab)

  3. Predictive Duty Cycling of Radios and Cameras using Augmented Sensing in Wireless Camera Networks

    … every aspect of the design of wireless camera networks (WCNs), and duty cycling of radios and cameras is an important tool for achieving high energy efficiencies. However, duty cycling in WCNs is made complex by the camera nodes having to anticipate the arrival of the objects in their …

    purdue-thes Repository record for Predictive Duty Cycling of Radios and Cameras using Augmented Sensing in Wireless Camera Networks (opens in a new tab)

  4. Autonomous Cyber Defense for Resilient Cyber-Physical Systems

    … cyber-physical systems (CPSs) under high network dynamics, adversarial attacks, and various uncertainties. We focus on three key system attributes to build resilient CPSs by developing a suite of the autonomous cyber defense mechanisms. First, we consider network adaptability to achieve …

    vt Repository record for Autonomous Cyber Defense for Resilient Cyber-Physical Systems (opens in a new tab)