By Topic

Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on

Issue 3 • Date June 2005

Filter Results

Displaying Results 1 - 25 of 25
  • Table of contents

    Publication Year: 2005 , Page(s): c1 - 481
    Save to Project icon | Request Permissions | PDF file iconPDF (116 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics publication information

    Publication Year: 2005 , Page(s): c2
    Save to Project icon | Request Permissions | PDF file iconPDF (35 KB)  
    Freely Available from IEEE
  • Non-Gaussian velocity distributions integrated over space, time, and scales

    Publication Year: 2005 , Page(s): 482 - 493
    Cited by:  Papers (7)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (794 KB) |  | HTML iconHTML  

    Velocity distributions are an enhanced representation of image velocity containing more velocity information than velocity vectors. In particular, non-Gaussian velocity distributions allow for the representation of ambiguous motion information caused by the aperture problem or multiple motions at motion boundaries. To resolve motion ambiguities, discrete non-Gaussian velocity distributions are suggested, which are integrated over space, time, and scales using a joint Bayesian prediction and refinement approach. This leads to a hierarchical velocity-distribution representation from which robust velocity estimates for both slow and high speeds as well as statistical confidence measures rating the velocity estimates can be computed. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fuzzy approach to the intelligent management of virtual spaces

    Publication Year: 2005 , Page(s): 494 - 508
    Cited by:  Papers (1)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (668 KB) |  | HTML iconHTML  

    This paper presents research carried out toward the improvement of current virtual environments from an intelligent systems approach. A novel architecture to solve vague queries that allows users to find objects and scenes in virtual environments is described. As a base, a new virtual worlds representation model and an associated fuzzy querying approach are used. The new representation model adds a semantic level to the usual models, providing more suitable environments for the interaction with users. The query solver is able to work with queries expressing the vagueness inherent to human conceptualization of visual perception (for example, tall tree, a park with many tall trees, or a park bench near approximately five tall trees). The system has been developed and evaluated with user experiments, where comparison with navigation and keyword-based query approaches have been realized. The results of this study show that the proposed architecture is more powerful and intuitive for finding the targets. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Mode-independent robust stabilization for uncertain Markovian jump nonlinear systems via fuzzy control

    Publication Year: 2005 , Page(s): 509 - 519
    Cited by:  Papers (31)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (205 KB) |  | HTML iconHTML  

    This paper is concerned with the robust-stabilization problem of uncertain Markovian jump nonlinear systems (MJNSs) without mode observations via a fuzzy-control approach. The Takagi and Sugeno (T-S) fuzzy model is employed to represent a nonlinear system with norm-bounded parameter uncertainties and Markovian jump parameters. The aim is to design a mode-independent fuzzy controller such that the closed-loop Markovian jump fuzzy system (MJFS) is robustly stochastically stable. Based on a stochastic Lyapunov function, a robust-stabilization condition using a mode-independent fuzzy controller is derived for the uncertain MJFS in terms of linear matrix inequalities (LMIs). A new improved LMI formulation is used to alleviate the interrelation between the stochastic Lyapunov matrix and the system matrices containing controller variables in the derivation process. Finally, a simulation example is presented to illustrate the effectiveness of the proposed design method. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Inducing NNC-trees with the R4-rule

    Publication Year: 2005 , Page(s): 520 - 533
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (474 KB) |  | HTML iconHTML  

    An NNC-Tree is a decision tree (DT) with each nonterminal node containing a nearest neighbor classifier (NNC). Compared with the conventional axis-parallel DTs (APDTs), the NNC-Trees can be more efficient, because the decision boundary made by an NNC is more complex than an axis-parallel hyperplane. Compared with single-layer NNCs, the NNC-Trees can classify given data in a hierarchical structure that is often useful for many applications. This paper proposes an algorithm for inducing NNC-Trees based on the R4-rule, which was proposed by the author for finding the smallest nearest neighbor based multilayer perceptrons (NN-MLPs). There are mainly two contributions here. 1) A heuristic but effective method is given to define the teacher signals (group labels) for the data assigned to each nonterminal node. 2) The R4-rule is modified so that an NNC with proper size can be designed automatically in each nonterminal node. Experiments with several public databases show that the proposed algorithm can produce NNC-Trees effectively and efficiently. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Hybridization of evolutionary algorithms and local search by means of a clustering method

    Publication Year: 2005 , Page(s): 534 - 545
    Cited by:  Papers (21)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (304 KB)  

    This paper presents a hybrid evolutionary algorithm (EA) to solve nonlinear-regression problems. Although EAs have proven their ability to explore large search spaces, they are comparatively inefficient in fine tuning the solution. This drawback is usually avoided by means of local optimization algorithms that are applied to the individuals of the population. The algorithms that use local optimization procedures are usually called hybrid algorithms. On the other hand, it is well known that the clustering process enables the creation of groups (clusters) with mutually close points that hopefully correspond to relevant regions of attraction. Local-search procedures can then be started once in every such region. This paper proposes the combination of an EA, a clustering process, and a local-search procedure to the evolutionary design of product-units neural networks. In the methodology presented, only a few individuals are subject to local optimization. Moreover, the local optimization algorithm is only applied at specific stages of the evolutionary process. Our results show a favorable performance when the regression method proposed is compared to other standard methods. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Inference in multiply sectioned Bayesian networks: methods and performance comparison

    Publication Year: 2005 , Page(s): 546 - 558
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (412 KB) |  | HTML iconHTML  

    This paper extends lazy propagation for inference in single-agent Bayesian networks (BNs) to multiagent lazy inference in multiply sectioned BNs (MSBNs). Two methods are proposed using distinct runtime structures. It was proved that the new methods are exact and efficient when the domain structure is sparse. Both improve space and time complexity more than the existing method, which allows multiagent probabilistic reasoning to be performed in much larger domains given the computational resource. The relative performances of the three methods are compared analytically and experimentally. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Evolutionary neural networks for anomaly detection based on the behavior of a program

    Publication Year: 2005 , Page(s): 559 - 570
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (877 KB) |  | HTML iconHTML  

    The process of learning the behavior of a given program by using machine-learning techniques (based on system-call audit data) is effective to detect intrusions. Rule learning, neural networks, statistics, and hidden Markov models (HMMs) are some of the kinds of representative methods for intrusion detection. Among them, neural networks are known for good performance in learning system-call sequences. In order to apply this knowledge to real-world problems successfully, it is important to determine the structures and weights of these call sequences. However, finding the appropriate structures requires very long time periods because there are no suitable analytical solutions. In this paper, a novel intrusion-detection technique based on evolutionary neural networks (ENNs) is proposed. One advantage of using ENNs is that it takes less time to obtain superior neural networks than when using conventional approaches. This is because they discover the structures and weights of the neural networks simultaneously. Experimental results with the 1999 Defense Advanced Research Projects Agency (DARPA) Intrusion Detection Evaluation (IDEVAL) data confirm that ENNs are promising tools for intrusion detection. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Balancing search and target response in cooperative unmanned aerial vehicle (UAV) teams

    Publication Year: 2005 , Page(s): 571 - 587
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (357 KB) |  | HTML iconHTML  

    This paper considers a heterogeneous team of cooperating unmanned aerial vehicles (UAVs) drawn from several distinct classes and engaged in a search and action mission over a spatially extended battlefield with targets of several types. During the mission, the UAVs seek to confirm and verifiably destroy suspected targets and discover, confirm, and verifiably destroy unknown targets. The locations of some (or all) targets are unknown a priori, requiring them to be located using cooperative search. In addition, the tasks to be performed at each target location by the team of cooperative UAVs need to be coordinated. The tasks must, therefore, be allocated to UAVs in real time as they arise, while ensuring that appropriate vehicles are assigned to each task. Each class of UAVs has its own sensing and attack capabilities, so the need for appropriate assignment is paramount. In this paper, an extensive dynamic model that captures the stochastic nature of the cooperative search and task assignment problems is developed, and algorithms for achieving a high level of performance are designed. The paper focuses on investigating the value of predictive task assignment as a function of the number of unknown targets and number of UAVs. In particular, it is shown that there is a tradeoff between search and task response in the context of prediction. Based on the results, a hybrid algorithm for switching the use of prediction is proposed, which balances the search and task response. The performance of the proposed algorithms is evaluated through Monte Carlo simulations. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Modeling emotional content of music using system identification

    Publication Year: 2005 , Page(s): 588 - 599
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (475 KB) |  | HTML iconHTML  

    Research was conducted to develop a methodology to model the emotional content of music as a function of time and musical features. Emotion is quantified using the dimensions valence and arousal, and system-identification techniques are used to create the models. Results demonstrate that system identification provides a means to generalize the emotional content for a genre of music. The average R2 statistic of a valid linear model structure is 21.9% for valence and 78.4% for arousal. The proposed method of constructing models of emotional content generalizes previous time-series models and removes ambiguity from classifiers of emotion. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multiperiod cellular network design via price-influenced simulated annealing (PISA)

    Publication Year: 2005 , Page(s): 600 - 610
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (353 KB) |  | HTML iconHTML  

    Cellular telecommunications systems tend to be more flexible than traditional ones. As a result, traditional approaches to telecommunications network design are often inappropriate for the design of cellular networks, and approaches that explicitly incorporate the increased flexibility into the design process need to be developed. This paper presents one such multiperiod cellular network design problem and solves it via a hybrid heuristic that incorporates ideas from linear programming (LP) and simulated annealing (SA). Extensive computational results comparing the performance of the heuristic with the lower bound obtained from the LP relaxation are presented. These results indicate that this price-influenced simulated annealing (PISA) procedure is extremely efficient, consistently providing solutions with average gaps of 0.30% or less in fewer than 30 s. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • On optimizing syntactic pattern recognition using tries and AI-based heuristic-search strategies

    Publication Year: 2005 , Page(s): 611 - 622
    Cited by:  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (518 KB)  

    This paper deals with the problem of estimating, using enhanced artificial-intelligence (AI) techniques, a transmitted string X* by processing the corresponding string Y, which is a noisy version of X*. It is assumed that Y contains substitution, insertion, and deletion (SID) errors. The best estimate X+ of X* is defined as that element of a dictionary H that minimizes the generalized Levenshtein distance (GLD) D(X,Y) between X and Y, for all X∈H. In this paper, it is shown how to evaluate D(X,Y) for every X∈H simultaneously, when the edit distances are general and the maximum number of errors is not given a priori, and when H is stored as a trie. A new scheme called clustered beam search (CBS) is first introduced, which is a heuristic-based search approach that enhances the well-known beam-search (BS) techniques used in AI. The new scheme is then applied to the approximate string-matching problem when the dictionary is stored as a trie. The new technique is compared with the benchmark depth-first search (DFS) trie-based technique (with respect to time and accuracy) using large and small dictionaries. The results demonstrate a marked improvement of up to 75% with respect to the total number of operations needed on three benchmark dictionaries, while yielding an accuracy comparable to the optimal. Experiments are also done to show the benefits of the CBS over the BS when the search is done on the trie. The results also demonstrate a marked improvement (more than 91%) for large dictionaries. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A self-organizing CMAC network with gray credit assignment

    Publication Year: 2005 , Page(s): 623 - 635
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (354 KB) |  | HTML iconHTML  

    This paper attempts to incorporate the structure of the cerebellar-model-articulation-controller (CMAC) network into the Kohonen layer of the self-organizing map (SOM) to construct a self-organizing CMAC (SOCMAC) network. The proposed SOCMAC network can perform the function of an SOM and can distribute the learning error into the memory contents of all addressed hypercubes as a CMAC. The learning of the SOCMAC is in an unsupervised manner. The neighborhood region of the SOCMAC is implicit in the structure of a two-dimensional CMAC network and needs not be defined in advance. Based on gray relational analysis, a credit-assignment technique for SOCMAC learning is introduced to hasten the overall learning process. This paper also analyzes the convergence properties of the SOCMAC. It is shown that under the proposed updating rule, both the memory contents and the state outputs of the SOCMAC converge almost surely. The SOCMAC is applied to solve both data-clustering and data-classification problems, and simulation results show that the proposed network achieves better performance than other known SOMs. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Variations over the message computation algorithm of lazy propagation

    Publication Year: 2005 , Page(s): 636 - 648
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (378 KB) |  | HTML iconHTML  

    Improving the performance of belief updating becomes increasingly important as real-world Bayesian networks continue to grow larger and more complex. In this paper, an investigation is done on how variations over the message-computation algorithm of lazy propagation may impact its performance. Lazy propagation is a junction-tree-based inference algorithm for belief updating in Bayesian networks. Lazy propagation combines variable elimination (VE) with a Shenoy-Shafer message-passing scheme in an attempt to exploit the independence properties induced by evidence in a junction-tree-based algorithm. The authors investigate, the use of arc reversal (AR) and symbolic probabilistic inference (SPI) as alternative algorithms for computing clique-to-clique messages in lazy propagation. The paper presents the results of an empirical evaluation of the performance of lazy propagation using AR, SPI, and VE as the message-computation algorithm. The results of the empirical evaluation show that no single algorithm outperforms or is outperformed by the other two alternatives. In many cases, there is no significant difference in the performance of the three algorithms. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Planar-shape prototype generation using a tree-based random greedy algorithm

    Publication Year: 2005 , Page(s): 649 - 659
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (309 KB) |  | HTML iconHTML  

    A prototype is representative of a set of similar objects. This paper proposes an approach that formulates the problem of prototype generation as finding the mean from a given set of objects, where the prototype solution must satisfy certain constraints. These constraints describe the important perceptual features of the sample shapes that the proposed prototype must retain. The contour prototype generated from a set of planar objects was used as an example of the approach, and the corners were used as the perceptual features to be preserved in the proposed prototype shape. However, finding a prototype solution for more than two contours is computationally intractable. A tree-based approach is therefore proposed in which an efficient greedy random algorithm is used to obtain a good approximation of the proposed prototype and analyze the expected complexity of the algorithm. The proposed prototype-generation process for hand-drawn patterns is described and discussed in this paper. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A functional-dependencies-based Bayesian networks learning method and its application in a mobile commerce system

    Publication Year: 2005 , Page(s): 660 - 671
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (366 KB) |  | HTML iconHTML  

    This paper presents a new method for learning Bayesian networks from functional dependencies (FD) and third normal form (3NF) tables in relational databases. The method sets up a linkage between the theory of relational databases and probabilistic reasoning models, which is interesting and useful especially when data are incomplete and inaccurate. The effectiveness and practicability of the proposed method is demonstrated by its implementation in a mobile commerce system. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An improved stability criterion for T-S fuzzy discrete systems via vertex expression

    Publication Year: 2005 , Page(s): 672 - 678
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (227 KB) |  | HTML iconHTML  

    The stability criteria for Takagi-Sugeno (T-S) fuzzy discrete systems based on a weighting-dependent Lyapunov function have been studied in numerous literature. Most of those results need to find r (number of rules) positive matrices Pis to satisfy r2 Lyapunov inequalities. This paper combines the ideas of group-fired rules, estimation of the maximum distance between two successive states of the system, and the vertex expression of any point in a region together, so that the relaxed stability that satisfies fewer Lyapunov inequalities is derived. Finally, an example is illustrated to reveal the merit of the proposed stability criterion. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fuzzy versus quantitative association rules: a fair data-driven comparison

    Publication Year: 2005 , Page(s): 679 - 684
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (165 KB) |  | HTML iconHTML  

    As opposed to quantitative association rule mining, fuzzy association rule mining is said to prevent the overestimation of boundary cases, as can be shown by small examples. Rule mining, however, becomes interesting in large databases, where the problem of boundary cases is less apparent and can be further suppressed by using sensible partitioning methods. A data-driven approach is used to investigate if there is a significant difference between quantitative and fuzzy association rules in large databases. The influence of the choice of a particular triangular norm in this respect is also examined. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Stability analysis and H controller design of fuzzy large-scale systems based on piecewise Lyapunov functions

    Publication Year: 2005 , Page(s): 685 - 698
    Cited by:  Papers (30)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (594 KB) |  | HTML iconHTML  

    This paper presents a novel approach to stability analysis of a fuzzy large-scale system in which the system is composed of a number of Takagi-Sugeno (T-S) fuzzy subsystems with interconnections. The stability analysis is based on Lyapunov functions that are continuous and piecewise quadratic. It is shown that the stability of the fuzzy large-scale systems can be established if a piecewise Lyapunov function can be constructed, and, moreover, the function can be obtained by solving a set of linear matrix inequalities (LMIs) that are numerically feasible. It is also demonstrated via a numerical example that the stability result based on the piecewise quadratic Lyapunov functions is less conservative than that based on the common quadratic Lyapunov functions. The H controllers can also be designed by solving a set of LMIs based on these powerful piecewise quadratic Lyapunov functions. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Hybrid approach of selecting hyperparameters of support vector machine for regression

    Publication Year: 2005 , Page(s): 699 - 709
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (832 KB)  

    To select the hyperparameters of the support vector machine for regression (SVR), a hybrid approach is proposed to determine the kernel parameter of the Gaussian kernel function and the epsilon value of Vapnik's ε-insensitive loss function. The proposed hybrid approach includes a competitive agglomeration (CA) clustering algorithm and a repeated SVR (RSVR) approach. Since the CA clustering algorithm is used to find the nearly "optimal" number of clusters and the centers of clusters in the clustering process, the CA clustering algorithm is applied to select the Gaussian kernel parameter. Additionally, an RSVR approach that relies on the standard deviation of a training error is proposed to obtain an epsilon in the loss function. Finally, two functions, one real data set (i.e., a time series of quarterly unemployment rate for West Germany) and an identification of nonlinear plant are used to verify the usefulness of the hybrid approach. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Spatiotemporal salient points for visual recognition of human actions

    Publication Year: 2005 , Page(s): 710 - 719
    Cited by:  Papers (60)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (621 KB) |  | HTML iconHTML  

    This paper addresses the problem of human-action recognition by introducing a sparse representation of image sequences as a collection of spatiotemporal events that are localized at points that are salient both in space and time. The spatiotemporal salient points are detected by measuring the variations in the information content of pixel neighborhoods not only in space but also in time. An appropriate distance metric between two collections of spatiotemporal salient points is introduced, which is based on the chamfer distance and an iterative linear time-warping technique that deals with time expansion or time-compression issues. A classification scheme that is based on relevance vector machines and on the proposed distance measure is proposed. Results on real image sequences from a small database depicting people performing 19 aerobic exercises are presented. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Have you visited lately? www.ieee.org

    Publication Year: 2005 , Page(s): 720
    Save to Project icon | Request Permissions | PDF file iconPDF (220 KB)  
    Freely Available from IEEE
  • IEEE Systems, Man, and Cybernetics Society Information

    Publication Year: 2005 , Page(s): c3
    Save to Project icon | Request Permissions | PDF file iconPDF (25 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics Information for authors

    Publication Year: 2005 , Page(s): c4
    Save to Project icon | Request Permissions | PDF file iconPDF (32 KB)  
    Freely Available from IEEE

Aims & Scope

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics focuses on cybernetics, including communication and control across humans, machines and organizations at the structural or neural level

 

This Transaction ceased production in 2012. The current retitled publication is IEEE Transactions on Cybernetics.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dr. Eugene Santos, Jr.
Thayer School of Engineering
Dartmouth College