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Showing 121-140 of 10,000 results
  1. First-Order Logic Based Formalism for Temporal Data Mining*

    In this article we define a formalism for a methodology that has as purpose the discovery of knowledge, represented in the form of general Horn...
    Paul Cotofrei, Kilian Stoffel in Foundations of Data Mining and knowledge Discovery
    Chapter
  2. Identification of Critical Values in Latent Semantic Indexing

    In this chapter we analyze the values used by Latent Semantic Indexing (LSI) for information retrieval. By manipulating the values in the Singular...
    April Kontostathis, William M. Pottenger, Brian D. Davison in Foundations of Data Mining and knowledge Discovery
    Chapter
  3. On-line Model Learning for Mobile Manipulations

    In control system design, modeling the control objects is the foundation of high performance controllers. In most cases, the model is unknown before...
    Yu Sun, Ning **, **dong Tan in Machine Learning and Robot Perception
    Chapter
  4. A Vision of the New Civilization Era

    This chapter is organized as follows. After stressing the importance of having a vision on the verge of the new era of knowledge civilization, we...
    Andrzej P. Wierzbicki, Yoshiteru Nakamori in Creative Space
    Chapter
  5. A New Role of Systems Science Informed Systems Approach

    This chapter is organized as follows. We show first that, while systems science is by its definition interdisciplinary, a split into soft systems...
    Andrzej P. Wierzbicki, Yoshiteru Nakamori in Creative Space
    Chapter
  6. 7 Geometrical Parameter Estimation and CF Recognition

    This chapter presents the estimator component of the autonomous compliant motion system (see Fig. 1.2). This component...
    Tine Lefebvre, Herman Bruyninckx, Joris De Schutter in Nonlinear Kalman Filtering for Force-Controlled Robot Tasks
    Chapter
  7. 3 Literature Survey: Bayesian Probability Theory

    This chapter presents some basic aspects of Bayesian probability theory [21, 153]. First of all, the difference between Bayesian and classical...
    Tine Lefebvre, Herman Bruyninckx, Joris De Schutter in Nonlinear Kalman Filtering for Force-Controlled Robot Tasks
    Chapter
  8. 8 Experiment: A Cube-In-Corner Assembly

    This chapter validates the theory of the previous chapters with an experiment. The experiment consists of the estimation of the geometrical...
    Tine Lefebvre, Herman Bruyninckx, Joris De Schutter in Nonlinear Kalman Filtering for Force-Controlled Robot Tasks
    Chapter
  9. Homogeneous Semantics Preserving Deployments of Heterogeneous Networks of Embedded Systems

    Tagged systems provide a denotational semantics for embedded systems. A heterogeneous network of embedded systems can be modeled mathematically by a...
    Aaron D. Ames, Alberto Sangiovanni-Vincentelli, Shankar Sastry in Networked Embedded Sensing and Control
    Chapter
  10. 6. Kinematic Control of UVMSs

    A robotic system is kinematically redundant when it possesses more degrees of freedom than those required to execute a given task. A generic...
    Gianluca Antonelli in Underwater Robots – 2nd Edition
    Chapter
  11. 6 Contact Modelling

    This chapter describes the contact modelling for autonomous compliant motion assuming quasi-static, rigid, frictionless contacts. The contact models...
    Tine Lefebvre, Herman Bruyninckx, Joris De Schutter in Nonlinear Kalman Filtering for Force-Controlled Robot Tasks
    Chapter
  12. E Partial Observation with the Kalman Filter

    This appendix contains the proofs of Lemmas 7.1 and 7.2. These lemmas state that, for static systems, (i) a Kalman Filter can be run on only the...
    Tine Lefebvre, Herman Bruyninckx, Joris De Schutter in Nonlinear Kalman Filtering for Force-Controlled Robot Tasks
    Chapter
  13. Distributed Kalman Filtering and Sensor Fusion in Sensor Networks

    The problem of distributed Kalman filtering (DKF) for sensor networks is one of the most fundamental distributed estimation problems for scalable...
    Chapter
  14. Applications of Connectivity Graph Processes in Networked Sensing and Control

    This paper concerns the problem of controlling mobile nodes in a network in such a way that the resulting graph-encoding of the inter-node...
    Abubakr Muhammad, Meng Ji, Magnus Egerstedt in Networked Embedded Sensing and Control
    Chapter
  15. Delay-Reliability Tradeoffs in Wireless Networked Control Systems

    Networked control systems (NCS) require the data to be communicated timely and reliably. However, random transmission errors incurred by wireless...
    Min **e, Martin Haenggi in Networked Embedded Sensing and Control
    Chapter
  16. Plenary Talk: The Role of Information Theory in Communication Constrained Control Systems

    Communication is an important component of distributed, networked, and cooperative control systems. In most current systems the communication aspects...
    Chapter
  17. Simulation of Large-Scale Networked Control Systems Using GTSNetS

    This paper presents a simulation framework for distributed control using wireless sensor networks. The proposed framework is an extension of the...
    ElMoustapha Ould-Ahmed-Vall, Bonnie S. Heck, George F. Riley in Networked Embedded Sensing and Control
    Chapter
  18. Belief Consensus and Distributed Hypothesis Testing in Sensor Networks

    In this paper, we address distributed hypothesis testing (DHT) in sensor networks and Bayesian networks using the average-consensus algorithm of...
    Reza Olfati-Saber, Elisa Franco, ... Je. S. Shamma in Networked Embedded Sensing and Control
    Chapter
  19. Plenary Talk Network-Embedded Sensing and Control: Applications and Application Requirements

    The first part of my talk will cover some recent commercially successful applications of networked and embedded sensing and control solutions. These...
    Chapter
  20. Research Issues in Web Structural Delta Mining

    Web structure mining has been a well-researched area during recent years. Based on the observation that data on the web may change at any time in any...
    Qiankun Zhao, Sourav S. Bhowmick, Sanjay Madria in Foundations and Novel Approaches in Data Mining
    Chapter
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