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# IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)

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Displaying Results 1 - 20 of 20

Publication Year: 2012, Page(s): C1
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• ### IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics publication information

Publication Year: 2012, Page(s): C2
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• ### Feature Selection With Harmony Search

Publication Year: 2012, Page(s):1509 - 1523
Cited by:  Papers (49)
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Many search strategies have been exploited for the task of feature selection (FS), in an effort to identify more compact and better quality subsets. Such work typically involves the use of greedy hill climbing (HC), or nature-inspired heuristics, in order to discover the optimal solution without going through exhaustive search. In this paper, a novel FS approach based on harmony search (HS) is pre... View full abstract»

• ### Reverse Control for Humanoid Robot Task Recognition

Publication Year: 2012, Page(s):1524 - 1537
Cited by:  Papers (7)
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Efficient methods to perform motion recognition have been developed using statistical tools. Those methods rely on primitive learning in a suitable space, for example, the latent space of the joint angle and/or adequate task spaces. Learned primitives are often sequential: A motion is segmented according to the time axis. When working with a humanoid robot, a motion can be decomposed into parallel... View full abstract»

• ### Approximate Optimal Control Design for Nonlinear One-Dimensional Parabolic PDE Systems Using Empirical Eigenfunctions and Neural Network

Publication Year: 2012, Page(s):1538 - 1549
Cited by:  Papers (27)
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This paper addresses the approximate optimal control problem for a class of parabolic partial differential equation (PDE) systems with nonlinear spatial differential operators. An approximate optimal control design method is proposed on the basis of the empirical eigenfunctions (EEFs) and neural network (NN). First, based on the data collected from the PDE system, the Karhunen-Loève decomp... View full abstract»

• ### An Effective Feature Selection Method via Mutual Information Estimation

Publication Year: 2012, Page(s):1550 - 1559
Cited by:  Papers (10)
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This paper proposes a new feature selection method using a mutual information-based criterion that measures the importance of a feature in a backward selection framework. It considers the dependency among many features and uses either one of two well-known probability density function estimation methods when computing the criterion. The proposed approach is compared with existing mutual informatio... View full abstract»

• ### Multivariate Multilinear Regression

Publication Year: 2012, Page(s):1560 - 1573
Cited by:  Papers (11)
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Conventional regression methods, such as multivariate linear regression (MLR) and its extension principal component regression (PCR), deal well with the situations that the data are of the form of low-dimensional vector. When the dimension grows higher, it leads to the under sample problem (USP): the dimensionality of the feature space is much higher than the number of training samples. However, l... View full abstract»

• ### ${cal H}_{infty}$ Model Reduction of Takagi–Sugeno Fuzzy Stochastic Systems

Publication Year: 2012, Page(s):1574 - 1585
Cited by:  Papers (93)
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This paper is concerned with the problem of H model reduction for Takagi-Sugeno (T-S) fuzzy stochastic systems. For a given mean-square stable T-S fuzzy stochastic system, our attention is focused on the construction of a reduced-order model, which not only approximates the original system well with an H performance but also translates it into a ... View full abstract»

• ### Joint-Structured-Sparsity-Based Classification for Multiple-Measurement Transient Acoustic Signals

Publication Year: 2012, Page(s):1586 - 1598
Cited by:  Papers (10)
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This paper investigates the joint-structured-sparsity-based methods for transient acoustic signal classification with multiple measurements. By joint structured sparsity, we not only use the sparsity prior for each measurement but we also exploit the structural information across the sparse representation vectors of multiple measurements. Several different sparse prior models are investigated in t... View full abstract»

• ### Robust Adaptive Control of MEMS Triaxial Gyroscope Using Fuzzy Compensator

Publication Year: 2012, Page(s):1599 - 1607
Cited by:  Papers (45)
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In this paper, a robust adaptive control strategy using a fuzzy compensator for MEMS triaxial gyroscope, which has system nonlinearities, including model uncertainties and external disturbances, is proposed. A fuzzy logic controller that could compensate for the model uncertainties and external disturbances is incorporated into the adaptive control scheme in the Lyapunov framework. The proposed ad... View full abstract»

• ### Neural-Network-Based Decentralized Adaptive Output-Feedback Control for Large-Scale Stochastic Nonlinear Systems

Publication Year: 2012, Page(s):1608 - 1619
Cited by:  Papers (122)
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This paper focuses on the problem of neural-network-based decentralized adaptive output-feedback control for a class of nonlinear strict-feedback large-scale stochastic systems. The dynamic surface control technique is used to avoid the explosion of computational complexity in the backstepping design process. A novel direct adaptive neural network approximation method is proposed to approximate th... View full abstract»

• ### Supervised Latent Linear Gaussian Process Latent Variable Model for Dimensionality Reduction

Publication Year: 2012, Page(s):1620 - 1632
Cited by:  Papers (6)
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The Gaussian process (GP) latent variable model (GPLVM) has the capability of learning low-dimensional manifold from highly nonlinear data of high dimensionality. As an unsupervised dimensionality reduction (DR) algorithm, the GPLVM has been successfully applied in many areas. However, in its current setting, GPLVM is unable to use label information, which is available for many tasks; therefore, r... View full abstract»

• ### Human-Arm-and-Hand-Dynamic Model With Variability Analyses for a Stylus-Based Haptic Interface

Publication Year: 2012, Page(s):1633 - 1644
Cited by:  Papers (11)
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Haptic interface research benefits from accurate human arm models for control and system design. The literature contains many human arm dynamic models but lacks detailed variability analyses. Without accurate measurements, variability is modeled in a very conservative manner, leading to less than optimal controller and system designs. This paper not only presents models for human arm dynamics but ... View full abstract»

• ### Optimization of Neural Networks Using Variable Structure Systems

Publication Year: 2012, Page(s):1645 - 1653
Cited by:  Papers (6)
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This paper proposes a new mixed training algorithm consisting of error backpropagation (EBP) and variable structure systems (VSSs) to optimize parameter updating of neural networks. For the optimization of the number of neurons in the hidden layer, a new term based on the output of the hidden layer is added to the cost function as a penalty term to make optimal use of hidden units related to weigh... View full abstract»

• ### Gait Recognition Across Various Walking Speeds Using Higher Order Shape Configuration Based on a Differential Composition Model

Publication Year: 2012, Page(s):1654 - 1668
Cited by:  Papers (20)
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Gait has been known as an effective biometric feature to identify a person at a distance. However, variation of walking speeds may lead to significant changes to human walking patterns. It causes many difficulties for gait recognition. A comprehensive analysis has been carried out in this paper to identify such effects. Based on the analysis, Procrustes shape analysis is adopted for gait signature... View full abstract»

• ### Linearithmic Time Sparse and Convex Maximum Margin Clustering

Publication Year: 2012, Page(s):1669 - 1692
Cited by:  Papers (3)
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Recently, a new clustering method called maximum margin clustering (MMC) was proposed and has shown promising performances. It was originally formulated as a difficult nonconvex integer problem. To make the MMC problem practical, the researchers either relaxed the original MMC problem to inefficient convex optimization problems or reformulated it to nonconvex optimization problems, which sacrifice... View full abstract»

• ### Adjustable Model-Based Fusion Method for Multispectral and Panchromatic Images

Publication Year: 2012, Page(s):1693 - 1704
Cited by:  Papers (41)
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In this paper, an adjustable model-based image fusion method for multispectral (MS) and panchromatic (PAN) images is developed. The relationships of the desired high spatial resolution (HR) MS images to the observed low-spatial-resolution MS images and HR PAN image are formulated with image observation models. The maximum a posteriori framework is employed to describe the inverse problem of image ... View full abstract»

• ### 2012 Index IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) Vol. 42

Publication Year: 2012, Page(s):1705 - 1723
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• ### IEEE Systems, Man, and Cybernetics Society Information

Publication Year: 2012, Page(s): C3
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• ### IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics information for authors

Publication Year: 2012, Page(s): C4
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## 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.

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## Meet Our Editors

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