# IEEE Transactions on Cybernetics

## Filter Results

Displaying Results 1 - 24 of 24

Publication Year: 2016, Page(s):C1 - 1485
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• ### IEEE Transactions on Cybernetics

Publication Year: 2016, Page(s): C2
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• ### MIRACLE: Mobility Prediction Inside a Coverage Hole Using Stochastic Learning Weak Estimator

Publication Year: 2016, Page(s):1486 - 1497
Cited by:  Papers (2)
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In target tracking applications of wireless sensor networks (WSNs), one of the important but overlooked issues is the estimation of mobility behavior of a target inside a coverage hole. The existing approaches are restricted to networks with effective coverage by wireless sensors. Additionally, those works implicitly considered that a target does not change its mobility pattern inside the entire t... View full abstract»

• ### Learning A Superpixel-Driven Speed Function for Level Set Tracking

Publication Year: 2016, Page(s):1498 - 1510
Cited by:  Papers (6)
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A key problem in level set tracking is to construct a discriminative speed function for effective contour evolution. In this paper, we propose a level set tracking method based on a discriminative speed function, which produces a superpixel-driven force for effective level set evolution. Based on kernel density estimation and metric learning, the speed function is capable of effectively encoding t... View full abstract»

• ### Adaptive Robust Online Constructive Fuzzy Control of a Complex Surface Vehicle System

Publication Year: 2016, Page(s):1511 - 1523
Cited by:  Papers (84)
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In this paper, a novel adaptive robust online constructive fuzzy control (AR-OCFC) scheme, employing an online constructive fuzzy approximator (OCFA), to deal with tracking surface vehicles with uncertainties and unknown disturbances is proposed. Significant contributions of this paper are as follows: 1) unlike previous self-organizing fuzzy neural networks, the OCFA employs decoupled distance mea... View full abstract»

• ### Crowd Event Detection on Optical Flow Manifolds

Publication Year: 2016, Page(s):1524 - 1537
Cited by:  Papers (8)
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Analyzing crowd events in a video is key to understanding the behavioral characteristics of people (humans). Detecting crowd events in videos is challenging because of articulated human movements and occlusions. The aim of this paper is to detect the events in a probabilistic framework for automatically interpreting the visual crowd behavior. In this paper, crowd event detection and classification... View full abstract»

• ### Dynamic Neural Networks for Kinematic Redundancy Resolution of Parallel Stewart Platforms

Publication Year: 2016, Page(s):1538 - 1550
Cited by:  Papers (18)
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Redundancy resolution is a critical problem in the control of parallel Stewart platform. The redundancy endows us with extra design degree to improve system performance. In this paper, the kinematic control problem of Stewart platforms is formulated to a constrained quadratic programming. The Karush-Kuhn-Tucker conditions of the problem is obtained by considering the problem in its dual space, and... View full abstract»

• ### High-Speed General Purpose Genetic Algorithm Processor

Publication Year: 2016, Page(s):1551 - 1565
Cited by:  Papers (7)
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In this paper, an ultrafast steady-state genetic algorithm processor (GAP) is presented. Due to the heavy computational load of genetic algorithms (GAs), they usually take a long time to find optimum solutions. Hardware implementation is a significant approach to overcome the problem by speeding up the GAs procedure. Hence, we designed a digital CMOS implementation of GA in 0.18 μm process. The pr... View full abstract»

• ### Reaching Synchronization in Networked Harmonic Oscillators With Outdated Position Data

Publication Year: 2016, Page(s):1566 - 1578
Cited by:  Papers (15)
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This paper studies the synchronization problem for a network of coupled harmonic oscillators by proposing a distributed control algorithm based only on delayed position states, i.e., outdated position states stored in memory. The coupling strength of the network is conveniently designed according to the absolute values and the principal arguments of the nonzero eigenvalues of the network Laplacian... View full abstract»

• ### Synchronization of a Group of Mobile Agents With Variable Speeds Over Proximity Nets

Publication Year: 2016, Page(s):1579 - 1590
Cited by:  Papers (1)
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This paper focuses on the synchronization analysis of a class of multiagent systems, where both speed and heading of each agent depend on the states of its local neighbors. The neighbors are defined through the distance between agents and all agents are interconnected via proximity nets. In the variable speed model, the speed of each agent depends on the polarization order of its neighbors in a po... View full abstract»

• ### Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems

Publication Year: 2016, Page(s):1591 - 1601
Cited by:  Papers (139)
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Combined with backstepping techniques, an observer-based adaptive consensus tracking control strategy is developed for a class of high-order nonlinear multiagent systems, of which each follower agent is modeled in a semi-strict-feedback form. By constructing the neural network-based state observer for each follower, the proposed consensus control method solves the unmeasurable state problem of hig... View full abstract»

• ### View Transformation Model Incorporating Quality Measures for Cross-View Gait Recognition

Publication Year: 2016, Page(s):1602 - 1615
Cited by:  Papers (26)
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Cross-view gait recognition authenticates a person using a pair of gait image sequences with different observation views. View difference causes degradation of gait recognition accuracy, and so several solutions have been proposed to suppress this degradation. One useful solution is to apply a view transformation model (VTM) that encodes a joint subspace of multiview gait features trained with aux... View full abstract»

• ### High-Order Energies for Stereo Segmentation

Publication Year: 2016, Page(s):1616 - 1627
Cited by:  Papers (15)
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In this paper, we propose a novel segmentation approach for stereo images using the high-order energy optimization, which utilizes the disparity maps and statistical information of stereo images to enrich the high-order potential functions. To the best of our knowledge, our approach is the first one to formulate the problem of stereo segmentation as a high-order energy optimization problem, which ... View full abstract»

• ### $F$-Discrepancy for Efficient Sampling in Approximate Dynamic Programming

Publication Year: 2016, Page(s):1628 - 1639
Cited by:  Papers (5)
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In this paper, we address the problem of generating efficient state sample points for the solution of continuous-state finite-horizon Markovian decision problems through approximate dynamic programming. It is known that the selection of sampling points at which the value function is observed is a key factor when such function is approximated by a model based on a finite number of evaluations. A st... View full abstract»

• ### Learning Stationary Correlated Equilibria in Constrained General-Sum Stochastic Games

Publication Year: 2016, Page(s):1640 - 1654
Cited by:  Papers (3)
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We study constrained general-sum stochastic games with unknown Markovian dynamics. A distributed constrained no-regret Q-learning scheme (CNRQ) is presented to guarantee convergence to the set of stationary correlated equilibria of the game. Prior art addresses the unconstrained case only, is structured with nested control loops, and has no convergence result. CNRQ is cast as a single-loop three-t... View full abstract»

• ### Distributed Optimization for a Class of Nonlinear Multiagent Systems With Disturbance Rejection

Publication Year: 2016, Page(s):1655 - 1666
Cited by:  Papers (28)
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The paper studies the distributed optimization problem for a class of nonlinear multiagent systems in the presence of external disturbances. To solve the problem, we need to achieve the optimal multiagent consensus based on local cost function information and neighboring information and meanwhile to reject local disturbance signals modeled by an exogenous system. With convex analysis and the inter... View full abstract»

• ### Learning Hierarchical Spectral–Spatial Features for Hyperspectral Image Classification

Publication Year: 2016, Page(s):1667 - 1678
Cited by:  Papers (25)
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This paper proposes a spectral-spatial feature learning (SSFL) method to obtain robust features of hyperspectral images (HSIs). It combines the spectral feature learning and spatial feature learning in a hierarchical fashion. Stacking a set of SSFL units, a deep hierarchical model called the spectral-spatial networks (SSN) is further proposed for HSI classification. SSN can exploit both discrimina... View full abstract»

• ### Identification-Based Closed-Loop NMES Limb Tracking With Amplitude-Modulated Control Input

Publication Year: 2016, Page(s):1679 - 1690
Cited by:  Papers (3)
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An upper motor neuron lesion (UMNL) can be caused by various neurological disorders or trauma and leads to disabilities. Neuromuscular electrical stimulation (NMES) is a technique that is widely used for rehabilitation and restoration of motor function for people suffering from UMNL. Typically, stability analysis for closed-loop NMES ignores the modulated implementation of NMES. However, electrica... View full abstract»

• ### Learning the Inverse Dynamics of Robotic Manipulators in Structured Reproducing Kernel Hilbert Space

Publication Year: 2016, Page(s):1691 - 1703
Cited by:  Papers (5)
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We investigate the modeling of inverse dynamics without prior kinematic information for holonomic rigid-body robots. Despite success in compensating robot dynamics and friction, general inverse dynamics models are nontrivial. Rigid-body models are restrictive or inefficient; learning-based models are generalizable yet require large training data. The structured kernels address the dilemma by embed... View full abstract»

• ### Multi-Step Ahead Predictions for Critical Levels in Physiological Time Series

Publication Year: 2016, Page(s):1704 - 1714
Cited by:  Papers (4)
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Standard modeling and evaluation methods have been classically used in analyzing engineering dynamical systems where the fundamental problem is to minimize the (mean) error between the real and predicted systems. Although these methods have been applied to multi-step ahead predictions of physiological signals, it is often more important to predict clinically relevant events than just to match thes... View full abstract»

• ### Introducing IEEE Collabratec

Publication Year: 2016, Page(s): 1715
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• ### Member Get-A-Member (MGM) Program

Publication Year: 2016, Page(s): 1716
| PDF (3461 KB)
• ### IEEE Transcations on Cybernetics society information

Publication Year: 2016, Page(s): C3
| PDF (151 KB)
• ### IEEE Transactions on Cybernetics information for author

Publication Year: 2016, Page(s): C4
| PDF (129 KB)

## Aims & Scope

The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Prof. Jun Wang
Dept. of Computer Science
City University of Hong Kong
Kowloon Tong, Kowloon, Hong Kong
Tel: +852 34429701
Email: jwang.cs@cityu.edu.hk