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Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on

Issue 1 • Date Jan 2001

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Displaying Results 1 - 9 of 9
  • New results on the performance of distributed Bayesian detection systems

    Page(s): 73 - 78
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (200 KB)  

    The purpose of decision fusion in a distributed detection system is to achieve a performance that is better than that of local detectors (or sensors). We consider a distributed Bayesian detection system consisting of n sensors and a fusion center, in which the decision rules of the sensors have been given and the decisions of different sensors are conditionally independent. We assume that the decision rules of the sensors can be optimum or suboptimum, and that the probabilities of detection and false alarm of the sensors can be different. Theoretical analysis on the performance of this fusion system is carried out. Conditions for the fusion system to achieve a global risk that is smaller than local risks are obtained View full abstract»

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  • Intelligent control for near-autonomous aircraft missions

    Page(s): 14 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (312 KB)  

    The focus of this paper is the design and implementation of a full envelope, nonlinear aircraft controller that includes stability augmentation, tracking control, and flight-path generation. The control system is demonstrated using a 6 degree-of-freedom (DOF) high performance aircraft model with nonlinear kinematics, full-envelope nonlinear aerodynamics, first-order thrust model, and first-order actuator dynamics. Ideas from the field of intelligent control were used in the definition of the controller architecture. More specifically, “levels of intelligent control” were used to provide a systematic structure for the architecture. Several ideas from the field of computational intelligence were also used including neural networks, genetic algorithms, and adaptive critics View full abstract»

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  • Some classification algorithms integrating Dempster-Shafer theory of evidence with the rank nearest neighbor rules

    Page(s): 59 - 66
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (292 KB)  

    We propose five different ways of integrating Dempster-Shafer theory of evidence and the rank nearest neighbor classification rules with a view to exploiting the benefits of both. These algorithms have been tested on both real and synthetic data sets and compared with the k-nearest neighbour rule (k-NN), m-multivariate rank nearest neighbour rule (m-MRNN), and k-nearest neighbour Dempster-Shafer theory rule (k-NNDST), which is an algorithm that also combines Dempster-Shafer theory with the k-NN rule. If different features have widely different variances then the distance-based classifier algorithms like k-NN and k-NNDST may not perform well, but in this case the proposed algorithms are expected to perform better. Our simulation results indeed reveal this. Moreover, the proposed algorithms are found to exhibit significant improvement over the m-MRNN rule View full abstract»

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  • Recovery of the metric structure of a pattern of points using minimal information

    Page(s): 30 - 42
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (272 KB)  

    A new method is proposed in order to reconstruct the geometrical configuration of a large points set using minimal information. The paper develops algorithms based on graph and kinematics theories to determine the minimum number of distances, needed to uniquely represent n points in d-dimensional Euclidean space. Therefore, it is found that this theoretical minimum is d(n-2)+1 interpoint distances. The method is evaluated, on the basis of basic parameters, by means of Monte Carlo simulation using genetic algorithms for better optimization procedures. This evaluation takes into account the real case where the metric informations are interpoint dissimilarities instead of exact Euclidean distances. Two applications on real data successfully illustrate the efficiency of the method. Finally, on the basis of Monte Carlo results, the authors provide some practical recommendations to experimenters who wish to use the method in order to scale a many-objects set View full abstract»

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  • Existence and construction of weight-set for satisfying preference orders of alternatives based on additive multi-attribute value model

    Page(s): 66 - 72
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (224 KB)  

    Based on the additive multi-attribute value model for multiple attribute decision making (MADM) problems, the paper investigates how the set of attribute weights (or weight-set thereafter) is determined according to the preference orders of alternatives given by decision makers. The weight-set is a bounded convex polyhedron and can be written as a convex combination of the extreme points. We give the sufficient and necessary conditions for the weight-set to be not empty and present the structures of the weight-set for satisfying the preference orders of alternatives. A method is also proposed to determine the weight-set. The structure of the weight-set is used to determine the interval of weights for every attribute in the decision analysis and to judge whether there exists a positive weight in the weight-set. The research results are applied to several MADM problems such as the geometric additive multi-attribute value model and the MADM problem with cone structure View full abstract»

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  • Teleoperation based on the hidden robot concept

    Page(s): 1 - 13
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (512 KB)  

    Overlaying classical teleoperation control schemes based on a bilateral master-slave coupling, a teleoperation architecture designed in a general teleworking context is proposed. In this scheme, the executing machine is perceptually and functionally hidden to the operator by means of an intermediate functional representation between a real remote world and man. As any executing machine, and more particularly a robot, will be replaced by man, the image of the robot will not appear in the intermediate representation. This principle is thus named: “the hidden robot concept.” In this approach, the teleoperation problem is divided into two main parts: 1) choosing the appropriate intermediate representation and determining its interaction and relation with man and 2) building the relations and transformations between the intermediate representation and the real remote environment. The constituents of this teleoperator are outlined in this paper and an experiment validating this concept is presented View full abstract»

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  • Experimental evaluation of policies for sequencing the presentation of associations

    Page(s): 55 - 59
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    Two policies for sequencing the presentation of associations are compared to the standard policy of randomly cycling through the list of associations. According to the modified-dropout policy, on each trial an association is presented that has not been presented on the two most recent trials and on which the observed number of correct responses since the last error is minimum. The second policy is based on a Markov state model of learning: on each trial, an association is presented that maximizes an arithmetic function of Bayesian estimates of residence in model states, a function that approximately indexes how unlearned associations are. Retention is improved relative to the standard policy only for the model-based policy View full abstract»

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  • On the performance of distributed Neyman-Pearson detection systems

    Page(s): 78 - 83
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    The performance of a distributed Neyman-Pearson detection system is considered. We assume that the decision rules of the sensors are given and that decisions from different sensors are mutually independent conditioned on both hypotheses. The purpose of decision fusion is to improve the performance of the overall system, and we are interested to know under what conditions can a better performance be achieved at fusion center, and under what conditions cannot. We assume that the probabilities of detection and false alarm of the sensors can be different. By comparing the probability of detection at fusion center with that of each of the sensors, with the probability of false alarm at fusion center constrained equal to that of the sensor, we give conditions for a better performance to be achieved at fusion center View full abstract»

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  • Providing synthetic views for teleoperation using visual pose tracking in multiple cameras

    Page(s): 43 - 54
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    This paper describes a visual tool for teleoperative experimentation involving remote manipulation and contact tasks. Using modest hardware, it recovers in real time the pose of moving polyhedral objects, and presents a synthetic view of the scene to the operator of a teleoperated robot using any chosen viewpoint and viewing direction. To recover pose, the method of line tracking first introduced by Harris (1992) is extended to multiple calibrated cameras, and its dynamic performance improved using robust methods and iterative filtering. Experiments are reported which determine the static and dynamic performance of the vision system, and its use in teleoperation is illustrated in two experiments, a peg-in-hole manipulation task and an impact control task View full abstract»

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Aims & Scope

The fields of systems engineering and human machine systems: systems engineering includes efforts that involve issue formulation, issue analysis and modeling, and decision making and issue interpretation at any of the lifecycle phases associated with the definition, development, and implementation of large systems.

 

This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dr. Witold Pedrycz
University of Alberta