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

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https://www.readbyqxmd.com/read/23292808/error-analysis-of-stochastic-gradient-descent-ranking
#1
Hong Chen, Yi Tang, Luoqing Li, Yuan Yuan, Xuelong Li, Yuanyan Tang
Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter...
December 31, 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22736648/adjustable-model-based-fusion-method-for-multispectral-and-panchromatic-images
#2
Liangpei Zhang, Huanfeng Shen, Wei Gong, Hongyan Zhang
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 fusion. By choosing particular probability density functions, the fused HR MS images are solved using a gradient descent algorithm...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22692923/human-arm-and-hand-dynamic-model-with-variability-analyses-for-a-stylus-based-haptic-interface
#3
Michael J Fu, M Cenk Cavuşoğlu
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 also develops inter- and intrasubject variability models for a stylus-based haptic device. Data from 15 human subjects (nine male, six female, ages 20-32) were collected using a Phantom Premium 1...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22677310/multivariate-multilinear-regression
#4
Ya Su, Xinbo Gao, Xuelong Li, Dacheng Tao
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, little attention has been paid to such a problem. This paper first adopts an in-depth investigation to the USP in PCR, which answers three questions: 1) Why is USP produced? 2) What is the condition for USP, and 3) How is the influence of USP on regression...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22665509/gait-recognition-across-various-walking-speeds-using-higher-order-shape-configuration-based-on-a-differential-composition-model
#5
Worapan Kusakunniran, Qiang Wu, Jian Zhang, Hongdong Li
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 description and relevant similarity measurement. To tackle the challenges raised by speed change, this paper proposes a higher order shape configuration for gait shape description, which deliberately conserves discriminative information in the gait signatures and is still able to tolerate the varying walking speed...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22665508/optimization-of-neural-networks-using-variable-structure-systems
#6
Seyed Alireza Mohseni, Ai Hui Tan
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 weights corresponding to each unit in the hidden layer. VSS is used to control the dynamic model of the training process, whereas EBP attempts to minimize the cost function...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22645273/linearithmic-time-sparse-and-convex-maximum-margin-clustering
#7
Xiao-Lei Zhang, Ji Wu
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 the convexity for efficiency. However, no approaches can both hold the convexity and be efficient. In this paper, a new linearithmic time sparse and convex MMC algorithm, called support-vector-regression-based MMC (SVR-MMC), is proposed...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22645272/feature-selection-with-harmony-search
#8
Ren Diao, Qiang Shen
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 presented. It is a general approach that can be used in conjunction with many subset evaluation techniques. The simplicity of HS is exploited to reduce the overall complexity of the search process...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22623433/supervised-latent-linear-gaussian-process-latent-variable-model-for-dimensionality-reduction
#9
Xinwei Jiang, Junbin Gao, Tianjiang Wang, Lihong Zheng
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, researchers proposed many kinds of extensions to the GPLVM in order to utilize extra information, among which the supervised GPLVM (SGPLVM) has shown better performance compared with other SGPLVM extensions...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22623432/neural-network-based-decentralized-adaptive-output-feedback-control-for-large-scale-stochastic-nonlinear-systems
#10
Qi Zhou, Peng Shi, Honghai Liu, Shengyuan Xu
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 the unknown and desired control input signals instead of the unknown nonlinear functions. It is shown that the designed controller can guarantee all the signals in the closed-loop system to be semiglobally uniformly ultimately bounded in a mean square...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22623431/h%C3%A2-model-reduction-of-takagi-sugeno-fuzzy-stochastic-systems
#11
Xiaojie Su, Ligang Wu, Peng Shi, Yong-Duan Song
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 linear lower dimensional system. Then, the model reduction is converted into a convex optimization problem by using a linearization procedure, and a projection approach is also presented, which casts the model reduction into a sequential minimization problem subject to linear matrix inequality constraints by employing the cone complementary linearization algorithm...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22614692/joint-structured-sparsity-based-classification-for-multiple-measurement-transient-acoustic-signals
#12
Haichao Zhang, Yanning Zhang, Nasser M Nasrabadi, Thomas S Huang
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 this paper to exploit the correlations among the multiple measurements with the notion of the joint structured sparsity for improving the classification accuracy...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22588610/approximate-optimal-control-design-for-nonlinear-one-dimensional-parabolic-pde-systems-using-empirical-eigenfunctions-and-neural-network
#13
Biao Luo, Huai-Ning Wu
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 decomposition is used to compute the EEFs. With those EEFs, the PDE system is formulated as a high-order ordinary differential equation (ODE) system...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22581140/an-effective-feature-selection-method-via-mutual-information-estimation
#14
Jian-Bo Yang, Chong-Jin Ong
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 information-based methods and another sophisticated filter method on many artificial and real-world problems. The numerical results show that the proposed method can effectively identify the important features in data sets having dependency among many features and is superior, in almost all cases, to the benchmark methods...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22575691/robust-adaptive-control-of-mems-triaxial-gyroscope-using-fuzzy-compensator
#15
Juntao Fei, Jian Zhou
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 adaptive fuzzy controller can guarantee the convergence and asymptotical stability of the closed-loop system. The proposed adaptive fuzzy control strategy does not depend on accurate mathematical models, which simplifies the design procedure...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22552575/reverse-control-for-humanoid-robot-task-recognition
#16
Sovannara Hak, Nicolas Mansard, Olivier Stasse, Jean Paul Laumond
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 subtasks. For example, in a waiter scenario, the robot has to keep some plates horizontal with one of its arms while placing a plate on the table with its free hand...
December 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22581138/global-bounded-consensus-of-multiagent-systems-with-nonidentical-nodes-and-time-delays
#17
Wei-Song Zhong, Guo-Ping Liu, Clive Thomas
This paper investigates the global bounded consensus problem of networked multiagent systems consisting of nonlinear nonidentical node dynamics with the communication time-delay topology. We derive globally bounded controlled consensus conditions for both delay-independent and delay-dependent conditions based on the Lyapunov-Krasovskii functional method. The proposed consensus criteria ensure that all agents eventually move along the desired trajectory in the sense of boundedness. Meanwhile, the bounded consensus criteria can be viewed as an extension of the case of identical agent dynamics to the case of nonidentical agent dynamics...
October 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22581136/multiresolution-motion-planning-for-autonomous-agents-via-wavelet-based-cell-decompositions
#18
Raghvendra V Cowlagi, Panagiotis Tsiotras
We present a path- and motion-planning scheme that is "multiresolution" both in the sense of representing the environment with high accuracy only locally and in the sense of addressing the vehicle kinematic and dynamic constraints only locally. The proposed scheme uses rectangular multiresolution cell decompositions, efficiently generated using the wavelet transform. The wavelet transform is widely used in signal and image processing, with emerging applications in autonomous sensing and perception systems. The proposed motion planner enables the simultaneous use of the wavelet transform in both the perception and in the motion-planning layers of vehicle autonomy, thus potentially reducing online computations...
October 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22562768/a-general-cpl-ads-methodology-for-fixing-dynamic-parameters-in-dual-environments
#19
De-Shuang Huang, Wen Jiang
The algorithm of Continuous Point Location with Adaptive d-ary Search (CPL-AdS) strategy exhibits its efficiency in solving stochastic point location (SPL) problems. However, there is one bottleneck for this CPL-AdS strategy which is that, when the dimension of the feature, or the number of divided subintervals for each iteration, d is large, the decision table for elimination process is almost unavailable. On the other hand, the larger dimension of the features d can generally make this CPL-AdS strategy avoid oscillation and converge faster...
October 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
https://www.readbyqxmd.com/read/22562767/crowd-motion-partitioning-in-a-scattered-motion-field
#20
Si Wu, Hau San Wong
In this paper, we propose a crowd motion partitioning approach based on local-translational motion approximation in a scattered motion field. To represent crowd motion in an accurate and parsimonious way, we compute optical flow at the salient locations instead of at all the pixel locations. We then transform the problem of crowd motion partitioning into a problem of scattered motion field segmentation. Based on our assumption that local crowd motion can be approximated by a translational motion field, we develop a local-translation domain segmentation (LTDS) model in which the evolution of domain boundaries is derived from the Gâteaux derivative of an objective functional and further extend LTDS to the case of scattered motion field...
October 2012: IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics
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