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Preface | |
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The Role of Dynamics in Extracting Information Sparsely Encoded in High Dimensional Data Streams | |
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Introduction | |
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Key Subproblems Arising in the Context of Dynamic Information Extraction | |
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Nonlinear Embedding of Dynamic Data | |
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Structure Extraction from High Dimensional Data Streams | |
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Robust Dynamic Data Segmentation | |
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Example 1: Video Segmentation | |
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Example 2: Segmentation of Dynamic Textures | |
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Constrained Interpolation of High Dimensional Signals | |
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Hypothesis Testing and Data Sharing | |
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Conclusions | |
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References | |
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Information Trajectory of Optimal Learning | |
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Introduction | |
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Topology and Geometry of Learning Systems | |
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Problem Statement and Basic Concepts | |
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Asymmetric Topologies and Gauge Functions | |
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Trajectories Continuous in Information | |
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Optimal Evolution and Bounds | |
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Empirical Evaluation on Learning Agents | |
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Conclusion | |
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References | |
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Performance-Information Analysis and Distributed Feedback Stabilization in Large-Scale Interconnected Systems | |
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Introduction | |
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Problem Formulation | |
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Performance-Information Analysis | |
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Problem Statements | |
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Distributed Risk-Averse Feedback Stabilization | |
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Conclusions | |
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References | |
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A General Approach for Modules Identification in Evolving Networks | |
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Introduction | |
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Preliminaries and Problem Definition | |
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Preliminaries | |
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Problem Definition | |
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Compact Representation of a Network | |
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Structure Preservation | |
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Size of the Compact Representation | |
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Partition Based on Evolution History | |
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Algorithm | |
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Complexity | |
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Experimental Evaluation | |
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Conclusions | |
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References | |
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Topology Information Control in Feedback Based Reconfiguration Processes | |
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Introduction and Motivation | |
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Group Communication Networking | |
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Reconfiguration Process Optimization | |
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Topology Information Model | |
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Information Control Problem | |
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Topology Information Control | |
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Lagrangian Solution | |
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Distributed Implementation | |
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Summary of Computational Results | |
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Concluding Remarks | |
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References | |
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Effect of Network Geometry and Interference on Consensus in Wireless Networks | |
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Introduction | |
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Problem Formulation | |
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Analysis of a Ring and a 2D Torus | |
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The 1-D Case: Nodes on a Ring | |
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Nodes on a Two-Dimensional Torus | |
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Hierarchical Networks | |
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Conclusions | |
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References | |
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Analyzing the Theoretical Performance of Information Sharing | |
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Introduction | |
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Information Sharing | |
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Token Algorithms | |
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Experimental Results | |
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Optimality of the Lookahead Policy | |
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Optimality of the Random Policies | |
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Effects of Noisy Estimation | |
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Properties Affecting Optimality | |
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Scaling Network Size | |
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Related Work | |
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Conclusions and Future Work | |
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References | |
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Self-Organized Criticality of Belief Propagation in Large Heterogeneous Teams | |
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Introduction | |
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Self-Organized Criticality | |
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Belief Sharing Model | |
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System Operation Regimes | |
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Simulation Results | |
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Related Work | |
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Conclusions and Future Work | |
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References | |
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Effect of Humans on Belief Propagation in Large Heterogeneous Teams | |
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Introduction | |
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Self-Organized Critical Systems | |
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The Enabler-Impeder Effect | |
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Model of Information Dissemination in a Network | |
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Simulation Results | |
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Related Work | |
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Conclusion and Future Work | |
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References | |
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Integration of Signals in Complex Biophysical Systems | |
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Introduction | |
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Methods for Analysis of Phase Synchronization | |
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Instantaneous Phase | |
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Phase Synchronization | |
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Generalized Phase Synchronization | |
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Analysis of the Data Collected During Sensory-Motor Experiments | |
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Sensory-Motor Experiments and Neural Data Acquisition | |
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Computational Analysis of the LFP Data | |
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Conclusion | |
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References | |
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An Info-Centric Trajectory Planner for Unmanned Ground Vehicles | |
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Introduction | |
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Problem Formulation and Background | |
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Obstacle Motion Studies | |
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The Sliding Door | |
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The Cyclic Sliding Door | |
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Obstacle Crossing (No Intercept) | |
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Obstacle Intercept | |
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Obstacle Intercept Window | |
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Target Motion Studies | |
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Target Rendezvous: Vehicle Faster than Target | |
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Target Rendezvous: Vehicle Slower than Target | |
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Target Rendezvous: Variable Target Motion | |
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Conclusion | |
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References | |
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Orbital Evasive Target Tracking and Sensor Management | |
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Introduction | |
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Fundamentals of Space Target Orbits | |
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Time and Coordinate Systems | |
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Orbital Equation and Orbital Parameter Estimation | |
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Modeling Maneuvering Target Motion in Space Target Tracking | |
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Sensor Measurement Model | |
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Game Theoretic Formulation for Target Maneuvering Onset Time | |
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Nonlinear Filter Design for Space Target Tracking | |
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Posterior Cramer-Rao Lower Bound of the State Estimation Error | |
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Sensor Management for Situation Awareness | |
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Information Theoretic Measure for Sensor Assignment | |
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Covariance Control for Sensor Scheduling | |
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Game Theoretic Covariance Prediction for Sensor Management | |
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Simulation Study | |
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Scenario Description | |
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Performance Comparison | |
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Summary and Conclusions | |
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References | |
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Decentralized Cooperative Control of Autonomous Surface Vehicles | |
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Introduction | |
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Motivation | |
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Decentralized Hierarchical Supervisor | |
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Persistent ISR Task | |
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Transit | |
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Simulation Results | |
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Conclusion and Future Work | |
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References | |
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A Connectivity Reduction Strategy for Multi-agent Systems | |
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Introduction | |
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Background | |
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Model | |
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Edge Robustness | |
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A Distributed Scheme of Graph Reduction | |
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Redundant Edges and Triangle Closures | |
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Local Triangle Topologies | |
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Distributed Algorithm | |
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Discussion and Simulation | |
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Conclusion | |
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References | |
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The Navigation Potential of Ground Feature Tracking | |
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Introduction | |
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Modeling | |
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Special Cases | |
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Nondimensional Variables | |
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Observability | |
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Only the Elevation z<sub>p</sub> of the Tracked Ground Object is Known | |
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Partial Observability | |
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Conclusion | |
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References | |
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Minimal Switching Time of Agent Formations with Collision Avoidance | |
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Introduction | |
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Problem Definition | |
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Dynamic Programming Formulation | |
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Derivation of the Dynamic Programming Recursion | |
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Collision Avoidance | |
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Computational Implementation | |
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Computational Experiments | |
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Conclusion | |
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References | |
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A Moving Horizon Estimator Performance Bound | |
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Introduction | |
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Linear State Estimation | |
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Kalman Filter as an IIR Filter | |
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Moving Average Implementation | |
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MHE Performance Bound | |
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Situation When A - K H A ≥ 1 | |
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Alternative Derivation | |
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Simulation and Analysis | |
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Simulation of Moving Horizon Estimator and Error Bound | |
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Monte Carlo Analysis of Error Bound | |
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Future Work | |
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References | |
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A p-norm Discrimination Model for Two Linearly Inseparable Sets | |
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Introduction | |
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The p-norm Linear Separation Model | |
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Implementation of p-order Conic Programming Problems via Polyhedral Approximations | |
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Polyhedral Approximations of p-order Cones | |
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"Tower-of-Variables" (Ben-Tal and Nemirovski [4]) | |
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Polyhedral Approximations of 3-dimensional p-order Cones | |
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Case Study | |
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Conclusions | |
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References | |
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Local Neighborhoods for the Multidimensional Assignment Problem | |
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Introduction | |
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Neighborhoods | |
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Intrapermutation Exchanges | |
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Interpermutation Exchanges | |
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Extensions | |
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Variable Depth Interchange | |
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Path Relinking | |
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Variable Neighborhood | |
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Discussion | |
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References | |