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Showing 1 to 9 of 9 for “"Network dynamic"”.

  1. Effective and Efficient Methodologies for Social Network Analysis

    Performing social network analysis (SNA) requires a set of powerful techniques to analyze structural information contained in interactions between social entities. Many SNA technologies and methodologies have been developed and have successfully provided significant insights for small-scale …

    vt Repository record for Effective and Efficient Methodologies for Social Network Analysis (opens in a new tab)

  2. Some decentralized optimization and control algorithms for the control of wind farms

    … We develop a stochastic algorithm based on network dynamic system theory to solve the resource allocation problem. We show that the algorithm converges to the solution of the resource allocation problem almost surely. The calculation of each wind turbine’s optimal control is formulated as an …

    uiuc Repository record for Some decentralized optimization and control algorithms for the control of wind farms (opens in a new tab)

  3. Hybrid Solutions for Mechatronics. Applications to modeling and controller design.

    … of modeling and controlling the evolution of dynamical sys- tems is one of the main objectives in mechatronics engineering. When approaching the problem of controlling physical or digital systems, the dynamical models have been historically divided into continuous-time, described by …

    trento Repository record for Hybrid Solutions for Mechatronics. Applications to modeling and controller design. (opens in a new tab)

  4. Dimension reduction methods for quantifying local variable importance and the statistical analysis of network data

    Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01

    uiuc Repository record for Dimension reduction methods for quantifying local variable importance and the statistical analysis of network data (opens in a new tab)

  5. Analysis and Design of Cognitive Radio Networks and Distributed Radio Resource Management Algorithms

    … frequently touted as a platform for implementing dynamic distributed radio resource management algorithms. In the envisioned scenarios, radios react to measurements of the network state and change their operation according to some goal driven algorithm. Ideally this flexibility and reactivity …

    vt Repository record for Analysis and Design of Cognitive Radio Networks and Distributed Radio Resource Management Algorithms (opens in a new tab)

  6. Deep Reinforcement Learning for Next Generation Wireless Networks with Echo State Networks

    … environments is to combine recurrent neural network (RNN) and DRL to capture temporal information inherent in the system, which is referred to as deep recurrent Q-network (DRQN). However, training DRQN is known to be challenging requiring a large amount of training data to achieve …

    vt Repository record for Deep Reinforcement Learning for Next Generation Wireless Networks with Echo State Networks (opens in a new tab)

  7. A novel storage area network (SAN) extension solution over passive optical networks (PONs)

    … grid failure in North America, storage area network (SAN) extension has emerged as a critical option to ensure business continuity. However, SAN extension encounters challenges in the access network including the scalability, cost, bandwidth bottleneck, and throughput. In this dissertation, a …

    njit Repository record for A novel storage area network (SAN) extension solution over passive optical networks (PONs) (opens in a new tab)

  8. Micromechanical study of two-phase flow during air sparging

    … in the porous medium is characterized by pore network consisting of connected pore bodies by bonds. Two approaches of generating 3D stochastic pore networks were proposed. The first methodology is to directly extract pore structure from a computer simulated packing of spheres. The second …

    njit Repository record for Micromechanical study of two-phase flow during air sparging (opens in a new tab)

  9. Statistical models and inference for dynamic networks

    … often best understood within the framework of networks. Network data can vary in many ways. For example, one might have binary or weighted networks, directed or undirected networks, and static or longitudinal networks. This last type of network, also called a dynamic network, is the focus of …

    uiuc Repository record for Statistical models and inference for dynamic networks (opens in a new tab)