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Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on

Issue 4 • Date Nov. 2002

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Displaying Results 1 - 25 of 27
  • Need to know-information, knowledge, and decision making

    Publication Year: 2002 , Page(s): 282 - 292
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (915 KB) |  | HTML iconHTML  

    The success of information and knowledge management depends on understanding and supporting the user's need to know. This requires understanding humans' abilities, limitations, and inclinations in seeking of information and knowledge. This paper explores these phenomena in the context of two decades of studying human decision making in the domains of research, design, and management. The findings summarized are discussed in terms of implications for design, development, and deployment of information and knowledge support systems. View full abstract»

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  • A LP-RR principle-based admission control for a mobile network

    Publication Year: 2002 , Page(s): 293 - 306
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (837 KB) |  | HTML iconHTML  

    In mobile networks, the traffic fluctuation is unpredictable due to mobility and varying resource requirement of multimedia applications. Hence, it is essential to maintain traffic within the network capacity to provide service guarantees to running applications. This paper proposes an admission control (AC) scheme in a mobile cellular environment supporting hand-off and new application traffic. In the case of multimedia applications, each applications has its own distinct range of acceptable quality of service (QoS) requirements. The network provides the service by maintaining the application specified QoS range. We propose a linear programming resource reduction (LP-RR) principle for admission control by maintaining QoS guarantees to existing applications and to increase the percentage of admission to hand-off and new applications. Artificial neural networks are used to solve the linear programming problem, which facilitates in real time admission control decision in the practical systems. We present an analytical model and results for the proposed AC scheme with resource reduction principle and a simulation study of the AC for performance evaluation. The simulation results demonstrate that the proposed AC scheme performs well in terms of increasing the number of admitted applications and maintains higher percentage of resource utilization. The suggested principle also shown that it is appropriate for the fair resource allocation with improved resource utilization. View full abstract»

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  • Hybrid artificial intelligence methods in oceanographic forecast models

    Publication Year: 2002 , Page(s): 307 - 313
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (232 KB) |  | HTML iconHTML  

    An approach to hybrid artificial intelligence problem solving is presented in which the aim is to forecast, in real time, the physical parameter values of a complex and dynamic environment: the ocean. In situations in which the rules that determine a system are unknown or fuzzy, the prediction of the parameter values that determine the characteristic behavior of the system can be a problematic task. In such a situation, it has been found that a hybrid artificial intelligence model can provide a more effective means of performing such predictions than either connectionist or symbolic techniques used separately. The hybrid forecasting system that has been developed consists of a case-based reasoning system integrated with a radial basis function artificial neural network. The results obtained from experiments in which the system operated in real time in the oceanographic environment, are presented. View full abstract»

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  • Petri nets and integrality relaxations: A view of continuous Petri net models

    Publication Year: 2002 , Page(s): 314 - 327
    Cited by:  Papers (44)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (648 KB) |  | HTML iconHTML  

    Petri nets are formalisms for the modeling of discrete event dynamic systems (DEDS). The integrality of the marking and of the transitions firing counters is a clear reflection of this. To reduce the computational complexity of the analysis or synthesis of Petri nets, two relaxations have been introduced at two different levels: (1) at net level, leading to continuous net systems; (2) at state equation level, which has allowed to obtain systems of linear inequalities, or linear programming problems. These relaxations are mainly related to the fractional firing of transitions, which implies the existence of non-integer markings. We give an overview of this emerging field. It is focused on the relationship between the properties of (discrete) PNs and the corresponding properties of their continuous approximation. Through the interleaving of qualitative and quantitative techniques, surprising results can be obtained from the analysis of these continuous systems. For these approximations to be "acceptable", it is necessary that large markings (populations) exist. It can also be seen, however, that not every populated net system can be continuized. In fact, there exist systems with "large" populations for which continuation does not make sense. The possibility of expressing nonlinear behaviors may lead to deterministic continuous differential systems with complex behaviors. View full abstract»

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  • Fuzzy decision tree, linguistic rules and fuzzy knowledge-based network: generation and evaluation

    Publication Year: 2002 , Page(s): 328 - 339
    Cited by:  Papers (28)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (867 KB)  

    A fuzzy knowledge-based network is developed based on the linguistic rules extracted from a fuzzy decision tree. A scheme for automatic linguistic discretization of continuous attributes, based on quantiles, is formulated. A novel concept for measuring the goodness of a decision tree, in terms of its compactness (size) and efficient performance, is introduced. Linguistic rules are quantitatively evaluated using new indices. The rules are mapped to a fuzzy knowledge-based network, incorporating the frequency of samples and depth of the attributes in the decision tree. New fuzziness measures, in terms of class memberships, are used at the node level of the tree to take care of overlapping classes. The effectiveness of the system, in terms of recognition scores, structure of decision tree, performance of rules, and network size, is extensively demonstrated on three sets of real-life data. View full abstract»

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  • Security PIDS with physical sensors, real-time pattern recognition, and continuous patrol

    Publication Year: 2002 , Page(s): 340 - 346
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (470 KB)  

    This perimeter intruder detection system (PIDS) is a system applicable to surveillance and perimeter control of areas of responsibility where risks are assessed, like swimming-pools, school precincts, museums, embassies, warehouses, and the like. It consists of a string of an arbitrary number of spaced but communicated micro-controllers, each one driving infra-red (IR) and/or ultrasound emitters and digital output transducers. The system uses radar effect and it carries continuous perimeter patrol by performing sequential surveillance of detector outputs as well as distributed pattern recognition analysis. All micro-controllers support a common code which includes turning the emitters sequentially on and off, pattern recognition routines, and serial transmission of alarm byte. Butterfly alarms are avoided via software and adequate geometrical configuration of the emitter beam net. One master micro-controller closes the string synchronizes and conducts the others. When the master micro-controller receives the "intruder" signal, it triggers the physical alarm, its next order being to restart patrolling. View full abstract»

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  • A distributed robotic control system based on a temporal self-organizing neural network

    Publication Year: 2002 , Page(s): 347 - 357
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (781 KB)  

    A distributed robot control system is proposed based on a temporal self-organizing neural network, called competitive and temporal Hebbian (CTH) network. The CTH network can learn and recall complex trajectories by means of two sets of synaptic weights, namely, competitive feedforward weights that encode the individual states of the trajectory and Hebbian lateral weights that encode the temporal order of trajectory states. Complex trajectories contain repeated or shared states which are responsible for ambiguities that occur during trajectory reproduction. Temporal context information are used to resolve such uncertainties. Furthermore, the CTH network saves memory space by maintaining only a single copy of each repeated/shared state of a trajectory and a redundancy mechanism improves the robustness of the network against noise and faults. The distributed control scheme is evaluated in point-to-point trajectory control tasks using a PUMA 560 robot. The performance of the control system is discussed and compared with other unsupervised and supervised neural network approaches. We also discuss the issues of stability and convergence of feedforward and lateral learning schemes. View full abstract»

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  • A prediction-based neural network scheme for lossless data compression

    Publication Year: 2002 , Page(s): 358 - 365
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (892 KB) |  | HTML iconHTML  

    This paper proposes a modified block-adaptive prediction-based neural network scheme for lossless data compression. A variety of neural network models from a selection of different network types, including feedforward, recurrent, and radial basis configurations are implemented with the scheme. The scheme is further expanded with combinations of popular lossless encoding algorithms. Simulation results are presented, taking characteristic features of the models, transmission issues, and practical considerations into account to determine optimized configuration, suitable training strategies, and implementation schemes. Estimations are used for comparisons of these characteristics with the existing schemes. It is also shown that the adaptations of the improvised scheme increases performance of even the classical predictors evaluated. In addition, the results obtained support that the total processing time of the two-stage scheme can, in certain cases, be faster than just using lossless encoders. Findings of the paper may be beneficial for future work, such as, in the hardware implementations of dedicated neural chips for lossless compression. View full abstract»

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  • An approach for organizing knowledge according to terminology and representing it visually

    Publication Year: 2002 , Page(s): 366 - 373
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (656 KB) |  | HTML iconHTML  

    We describe a term relation frequency (TRF) method for finding comprehensive documents in a rapidly growing academic discipline. The method enables us to organize knowledge into a single document based on terminology. The method is based on the classification of documents into comprehensive, central, peripheral, and independent classes according to the commonality and exclusiveness of terminology. Being able to find the documents quickly is helpful for our understanding of the discipline. Multiple-meaning technical terms such as "coordination" play a key role in rapidly growing academic disciplines such as coordination science. Visual representation of the multiple-meaning terms helps us to identify quickly and easily how the terms are used. With TRF and visualization methods, we can identify documents that explain a technical term comprehensively. We can also identify a change in the subject of a discipline according to when the comprehensive documents are written. We show that the observed change matches our understanding of the topic of the field "coordination science." The methods discussed here are promising to help us quickly understand and advance research in rapidly growing academic disciplines such as coordination science. View full abstract»

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  • Guaranteed robust nonlinear estimation with application to robot localization

    Publication Year: 2002 , Page(s): 374 - 381
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1202 KB)  

    When reliable prior bounds on the acceptable errors between the data and corresponding model outputs are available, bounded-error estimation techniques make it possible to characterize the set of all acceptable parameter vectors in a guaranteed way, even when the model is nonlinear and the number of data points small. However, when the data may contain outliers, i.e., data points for which these bounds should be violated, this set may turn out to be empty, or at least unrealistically small. The outlier minimal number estimator (OMNE) has been designed to deal with such a situation, by minimizing the number of data points considered as outliers. OMNE has been shown in previous papers to be remarkably robust, even to a majority of outliers. Up to now, it was implemented by random scanning, so its results could not be guaranteed. In this paper, a new algorithm based on set inversion via interval analysis provides a guaranteed OMNE, which is applied to the initial localization of an actual robot in a partially known two-dimensional (2-D) environment. The difficult problems of associating range data to landmarks of the environment and of detecting potential outliers are solved as byproducts of the procedure. View full abstract»

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  • Automatic construction of online catalog topologies

    Publication Year: 2002 , Page(s): 382 - 391
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (418 KB)  

    A good online catalog is crucial to the success of an e-commerce web site. Traditionally, an online catalog is mainly built by hand. To what extent this can be automated is a challenging problem. Recently, there have been investigations on how to reorganize an existing online catalog based on some criteria, but none of them has addressed the problem of organizing an online catalog automatically from scratch. This paper attempts to tackle this problem. We model an online catalog organization as a decision tree structure and propose a metric, based on the popularity of products and the relative importance of product attribute values, to evaluate the quality of a catalog organization. The problem is then formulated as a decision tree construction problem. Although traditional decision tree algorithms, such as C4.5, can be used to generate online catalog organization, the catalog constructed is generally not good based on our metric. An efficient greedy algorithm (GENCAT) is thus developed, and the experimental results show that GENCAT produces better catalog organizations based on our metric. View full abstract»

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  • Binocular transfer methods for point-feature tracking of image sequences

    Publication Year: 2002 , Page(s): 392 - 405
    Cited by:  Papers (2)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1316 KB)  

    Image transfer is a method for projecting a 3D scene from two or more reference images. Typically, the correspondences of target points to be transferred and the reference points must be known over the reference images. We present two new transfer methods that eliminate the target point correspondence requirement. We show that five reference points matched across two reference images are sufficient to linearly resolve transfer under affine projection using two views instead of three views as needed by other techniques. Furthermore, given the correspondences of any four of the five reference points in any other view, we can transfer a target point to a third view from any one of the two original reference views. To improve the robustness of the affine projection method, we incorporate an orthographic camera model. A factorization method is applied to the reference points matched over two reference views. Experiments with real image sequences demonstrate the application of both methods for motion tracking. View full abstract»

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  • An O(N) modular algorithm for the dynamic simulation of robots constrained by a single contact

    Publication Year: 2002 , Page(s): 406 - 415
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (487 KB) |  | HTML iconHTML  

    This paper presents an efficient modular algorithm for the dynamic simulation of robots constrained through a single contact. Such configurations include single robots with closed-loop topologies, as well as, multiple robots with simple series, parallel, and bracing topologies. The modular nature of the algorithm enables the incorporation of existing open-chain models for the individual robots without significant reprogramming, while a general contact model extends the range of possible contact conditions to include both holonomic and nonholonomic constraints. The algorithm is validated through the simulation of two robots cooperating in parallel. This paper establishes an accurate framework for simulating simple robot systems with single contacts, which can be extended to multi-robot, multi-contact systems performing general tasks. View full abstract»

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  • A high precision global prediction approach based on local prediction approaches

    Publication Year: 2002 , Page(s): 416 - 425
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (580 KB) |  | HTML iconHTML  

    Traditional model-free prediction approaches, such as neural networks or fuzzy models use all training data without preference in building their prediction models. Alternately, one may make predictions based only on a set of the most recent data without using other data. Usually, such local prediction schemes may have better performance in predicting time series than global prediction schemes do. However, local prediction schemes only use the most recent information and ignore information bearing on far away data. As a result, the accuracy of local prediction schemes may be limited. In this paper a novel prediction approach, termed the Markov-Fourier gray model (MFGM), is proposed. The approach builds a gray model from a set of the most recent data and a Fourier series is used to fit the residuals produced by this gray model. Then, the Markov matrices are employed to encode possible global information generated also by the residuals. It is evident that MFGM can provide the best performance among existing prediction schemes. Besides, we also implemented a short-term MFGM approach, in which the Markov matrices only recorded information for a period of time instead of all data. The predictions using MFGM again are more accurate than those using short-term MFGM. Thus, it is concluded that the global information encoded in the Markov matrices indeed can provide useful information for predictions. View full abstract»

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  • Bio-mimetic trajectory generation of robots via artificial potential field with time base generator

    Publication Year: 2002 , Page(s): 426 - 439
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (780 KB) |  | HTML iconHTML  

    This paper proposes a new trajectory generation method that allows full control of transient behavior, namely, time-to-target and velocity profile, based on the artificial potential field approach for a real-time robot motion planning problem. Little attention, in fact, has been paid to the temporal aspects of this class of path planning methods. The ability to control the motion time to the target as well as the velocity profile of the generated trajectories, however, is of great interest in real-life applications. In the paper, we argue that such transient behavior should be taken into account within the framework of the artificial potential field approach. View full abstract»

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  • Robust support vector machine with bullet hole image classification

    Publication Year: 2002 , Page(s): 440 - 448
    Cited by:  Papers (37)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (930 KB) |  | HTML iconHTML  

    This paper proposes a robust support vector machine for pattern classification, which aims at solving the over-fitting problem when outliers exist in the training data set. During the robust training phase, the distance between each data point and the center of class is used to calculate the adaptive margin. The incorporation of the average techniques to the standard support vector machine (SVM) training makes the decision function less detoured by outliers, and controls the amount of regularization automatically. Experiments for the bullet hole classification problem show that the number of the support vectors is reduced, and the generalization performance is improved significantly compared to that of the standard SVM training. View full abstract»

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  • Segmentation of touching characters in printed Devnagari and Bangla scripts using fuzzy multifactorial analysis

    Publication Year: 2002 , Page(s): 449 - 459
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (786 KB) |  | HTML iconHTML  

    One of the important reasons for poor recognition rate in optical character recognition (OCR) system is the error in character segmentation. Existence of touching characters in the scanned documents is a major problem to design an effective character segmentation procedure. In this paper, a new technique is presented for identification and segmentation of touching characters. The technique is based on fuzzy multifactorial analysis. A predictive algorithm is developed for effectively selecting possible cut columns for segmenting the touching characters. The proposed method has been applied to printed documents in Devnagari and Bangla: the two most popular scripts of the Indian sub-continent. The results obtained from a test-set of considerable size show that a reasonable improvement in recognition rate can be achieved with a modest increase in computations. View full abstract»

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  • Multiobjective evolutionary algorithm for the optimization of noisy combustion processes

    Publication Year: 2002 , Page(s): 460 - 473
    Cited by:  Papers (34)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (656 KB) |  | HTML iconHTML  

    This work introduces a multiobjective evolutionary algorithm capable of handling noisy problems with a particular emphasis on robustness against unexpected measurements (outliers). The algorithm is based on the Strength Pareto evolutionary algorithm of Zitzler and Thiele and includes the new concepts of domination dependent lifetime, re-evaluation of solutions and modifications in the update of the archive population. Several tests on prototypical functions underline the improvements in convergence speed and robustness of the extended algorithm. The proposed algorithm is implemented to the Pareto optimization of the combustion process of a stationary gas turbine in an industrial setup. The Pareto front is constructed for the objectives of minimization of NOx emissions and reduction of the pressure fluctuations (pulsation) of the flame. Both objectives are conflicting affecting the environment and the lifetime of the turbine, respectively. The optimization leads a Pareto front corresponding to reduced emissions and pulsation of the burner. The physical implications of the solutions are discussed and the algorithm is evaluated. View full abstract»

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  • Self-localizing dynamic microphone arrays

    Publication Year: 2002 , Page(s): 474 - 484
    Cited by:  Papers (21)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1380 KB) |  | HTML iconHTML  

    This paper introduces a mechanism for localizing a microphone array when the location of sound sources in the environment is known. Using the proposed spatial observability function based microphone array integration technique, a maximum likelihood estimator for the correct position and orientation of the array is derived. This is used to localize and track a microphone array with a known and fixed geometrical structure, which can be viewed as the inverse sound localization problem. Simulations using a two-element dynamic microphone array illustrate the ability of the proposed technique to correctly localize and estimate the orientation of the array even in a very reverberant environment. Using 1 s male speech segments from three speakers in a 7 m by 6 m by 2.5 m simulated environment, a 30 cm inter-microphone distance, and PHAT histogram SLF generation, the average localization error was approximately 3 cm with an average orientation error of 19°. The same simulation configuration but with 4 s speech segments results in an average localization error less than 1cm, with an average orientation error of approximately 2°. Experimental examples illustrate localizations for both stationary and dynamic microphone pairs. View full abstract»

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  • A generalized surveillance model with applications to systems safety

    Publication Year: 2002 , Page(s): 485 - 492
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (453 KB) |  | HTML iconHTML  

    This paper presents a generalized surveillance model for predicting the performance of complex systems consisting of many subsystems (units). These subsystems are frequently inspected to keep the entire system operating satisfactorily. Systems of this type are encountered in many areas, including nuclear power plant, national defense system, transportation stations, medical monitoring control rooms, etc. The particular application that motivated a development of this model is an FAA project, where we were asked to develop a surveillance model to better understand both the inspection process and the repair station itself and to provide information that can be used to assist inspectors in scheduling and prioritizing their visits to the stations. A distinguishing feature of this surveillance model is that it combines two mutually dependent stochastic processes. One is a two-stage stochastic process for the occurrence of unfavorable condition in an individual subsystem and the other is a nonhomogeneous Poisson process for the frequency of surveillance. View full abstract»

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  • Decentralized nonlinear adaptive control of an HVAC system

    Publication Year: 2002 , Page(s): 493 - 498
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (371 KB)  

    This paper presents a new decentralized nonlinear adaptive controller (DNAC) for a heating, ventilating, and air conditioning (HVAC) system capable of maintaining comfortable conditions under varying thermal loads. In this scheme, an HVAC system is considered to be two subsystems and controlled independently. The interactions between the two subsystems are treated as deterministic types of uncertain disturbances and their magnitudes are supposed to be bounded by absolute value. The decentralized nonlinear adaptive controller (DNAC) consists of an inner loop and an outer loop. The inner loop is a single-input fuzzy logic controller (FLC), which is used as the feedback controller to overcome random instant disturbances. The outer loop is a Fourier integral-based control, which is used as the frequency-domain adaptive compensator to overcome steady, lasting uncertain disturbances. The global DNAC controller ensures that the system output vector tracks a desired trajectory vector within the system bandwidth and that the tracking error vector converges uniformly to a zero vector. The simulated experimental results on the HVAC system show that the performance is dramatically improved. View full abstract»

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  • Classification of multispectral images based on a fuzzy-possibilistic neural network

    Publication Year: 2002 , Page(s): 499 - 506
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1404 KB) |  | HTML iconHTML  

    In this paper, a new Hopfield-model net based on fuzzy possibilistic reasoning is proposed for the classification of multispectral images. The main purpose is to modify the Hopfield network embedded with fuzzy possibilistic C-means (FPCM) method to construct a classification system named fuzzy-possibilistic Hopfield net (FPHN). The classification system is a paradigm for the implementation of fuzzy logic systems in neural network architecture. Instead of one state in a neuron for the conventional Hopfield nets, each neuron occupies 2 states called membership state and typicality state in the proposed FPHN. The proposed network not only solves the noise sensitivity fault of Fuzzy C-means (FCM) but also overcomes the simultaneous clustering problem of possibilistic C-means (PCM) strategy. In addition to the same characteristics as the FPCM algorithm, the simple features of this network are clear potential in optimal problem. The experimental results show that the proposed FPHN can obtain better solutions in the classification of multispectral images. View full abstract»

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  • Fault-tolerant gaits of quadruped robots for locked joint failures

    Publication Year: 2002 , Page(s): 507 - 516
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (544 KB) |  | HTML iconHTML  

    This paper lays a theoretical foundation for fault detection and tolerance in static walking of legged robots. Legged robots considered in this paper have symmetric structures and legs which have the form of an articulated arm with three revolute joints. A kind of fault event (locked joint failure) is defined, and its properties are closely investigated in the frame of gait study and robot kinematics. For the purpose of tolerating a locked joint failure, an algorithm of fault-tolerant gaits for a quadruped robot is proposed in which the robot can continue its walking after a locked failure occurs to a joint of a leg. In particular, a periodic gait is proposed as a special form of the proposed algorithm and its existence and efficiency are analytically proven. A case study on applying the proposed scheme to wave gaits verifies its applicability and capability. View full abstract»

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  • Application of an auto-tuning neuron to sliding mode control

    Publication Year: 2002 , Page(s): 517 - 522
    Cited by:  Papers (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (465 KB)  

    This paper presents a control strategy that incorporates an auto-tuning neuron into the sliding mode control (SMC) in order to eliminate the high control activity and chattering due to the SMC. The main difference between the auto-tuning neuron and the general one is that a modified hyperbolic tangent function with adjustable parameters is employed. In this proposed control structure, an auto-tuning neuron is then used as the neural controller without any connection weights.. The control law will be switched from the sliding control to the neural control, when the state trajectory of system enters in some boundary layer. In this way, the chattering phenomenon will not occur. The results of numerical simulations are provided to show the control performance of our proposed method. View full abstract»

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  • A symmetry-based coarse classification method for Chinese characters

    Publication Year: 2002 , Page(s): 522 - 528
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (542 KB)  

    In this paper, we present a novel symmetry-based coarse classification method for the preclassification of printed Chinese characters. The proposed method consists of two main modules, recursive radical extraction, and a symmetry test. The former classifies Chinese characters into ten classes according to the composing structure of the characters. Two classes in the ten classes, left-right, and up-down type characters, contain over 85% of the total characters. The latter performs the symmetry test to determine whether the character, or radical in the ten classes, is symmetric or not. The main purpose of the proposed symmetry-test coarse classification method is to reduce the number of characters in each of the ten classes. Four symmetry features are devised to perform the symmetry test. Experimental results reveal that the proposed method can greatly reduce the number of characters in each class to achieve the coarse classification goal. View full abstract»

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Aims & Scope

Overview, tutorial and application papers concerning all areas of interest to the SMC Society: systems engineering, human factors and human machine systems, and cybernetics and computational intelligence. 

Authors should submit human-machine systems papers to the IEEE Transactions on Human-Machine Systems.

Authors should submit systems engineering papers to the IEEE Transactions on Systems, Man and Cybernetics: Systems.

Authors should submit cybernetics papers to the IEEE Transactions on Cybernetics.

Authors should submit social system papers to the IEEE Transactions on Computational Social Systems.

 

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