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

Includes the top 50 most frequently accessed documents for this publication according to the usage statistics for the month of

• ### Extreme Learning Machine for Regression and Multiclass Classification

Publication Year: 2012, Page(s):513 - 529
Cited by:  Papers (1075)  |  Patents (2)
| | PDF (1244 KB) | HTML

Due to the simplicity of their implementations, least square support vector machine (LS-SVM) and proximal support vector machine (PSVM) have been widely used in binary classification applications. The conventional LS-SVM and PSVM cannot be used in regression and multiclass classification applications directly, although variants of LS-SVM and PSVM have been proposed to handle such cases. This paper... View full abstract»

• ### Evolving Fuzzy Rules for Relaxed-Criteria Negotiation

Publication Year: 2008, Page(s):1486 - 1500
Cited by:  Papers (14)
| | PDF (1330 KB) | HTML

In the literature on automated negotiation, very few negotiation agents are designed with the flexibility to slightly relax their negotiation criteria to reach a consensus more rapidly and with more certainty. Furthermore, these relaxed-criteria negotiation agents were not equipped with the ability to enhance their performance by learning and evolving their relaxed-criteria negotiation rules. The ... View full abstract»

• ### Adaptive Particle Swarm Optimization

Publication Year: 2009, Page(s):1362 - 1381
Cited by:  Papers (559)
| | PDF (895 KB) | HTML

An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perform a global search over the entire search space with faster convergence speed. The APSO consists of two main steps. First, by evaluating the population distribution and particle fitness, a real-time evolutionary state est... View full abstract»

• ### Multiclass Imbalance Problems: Analysis and Potential Solutions

Publication Year: 2012, Page(s):1119 - 1130
Cited by:  Papers (69)
| | PDF (1096 KB) | HTML

Class imbalance problems have drawn growing interest recently because of their classification difficulty caused by the imbalanced class distributions. In particular, many ensemble methods have been proposed to deal with such imbalance. However, most efforts so far are only focused on two-class imbalance problems. There are unsolved issues in multiclass imbalance problems, which exist in real-world... View full abstract»

• ### An EMG-Based Control for an Upper-Limb Power-Assist Exoskeleton Robot

Publication Year: 2012, Page(s):1064 - 1071
Cited by:  Papers (96)
| | PDF (1224 KB) | HTML

Many kinds of power-assist robots have been developed in order to assist self-rehabilitation and/or daily life motions of physically weak persons. Several kinds of control methods have been proposed to control the power-assist robots according to user's motion intention. In this paper, an electromyogram (EMG)-based impedance control method for an upper-limb power-assist exoskeleton robot is propos... View full abstract»

• ### Adaptive Sliding-Mode Control for NonlinearSystems With Uncertain Parameters

Publication Year: 2008, Page(s):534 - 539
Cited by:  Papers (139)
| | PDF (312 KB) | HTML

This correspondence proposes a systematic adaptive sliding- mode controller design for the robust control of nonlinear systems with uncertain parameters. An adaptation tuning approach without high- frequency switching is developed to deal with unknown but bounded system uncertainties. Tracking performance is guaranteed. System robustness, as well as stability, is proven by using the Lyapunov theor... View full abstract»

• ### Ant system: optimization by a colony of cooperating agents

Publication Year: 1996, Page(s):29 - 41
Cited by:  Papers (3872)  |  Patents (20)
| | PDF (1360 KB)

An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discover... View full abstract»

• ### Second-Order Consensus for Multiagent Systems With Directed Topologies and Nonlinear Dynamics

Publication Year: 2010, Page(s):881 - 891
Cited by:  Papers (377)
| | PDF (319 KB) | HTML

This paper considers a second-order consensus problem for multiagent systems with nonlinear dynamics and directed topologies where each agent is governed by both position and velocity consensus terms with a time-varying asymptotic velocity. To describe the system's ability for reaching consensus, a new concept about the generalized algebraic connectivity is defined for strongly connected networks ... View full abstract»

• ### Human-robot interactions during the robot-assisted urban search and rescue response at the World Trade Center

Publication Year: 2003, Page(s):367 - 385
Cited by:  Papers (280)  |  Patents (1)
| | PDF (2269 KB) | HTML

The World Trade Center (WTC) rescue response provided an unfortunate opportunity to study the human-robot interactions (HRI) during a real unstaged rescue for the first time. A post-hoc analysis was performed on the data collected during the response, which resulted in 17 findings on the impact of the environment and conditions on the HRI: the skills displayed and needed by robots and humans, the ... View full abstract»

• ### An Adaptive Differential Evolution Algorithm With Novel Mutation and Crossover Strategies for Global Numerical Optimization

Publication Year: 2012, Page(s):482 - 500
Cited by:  Papers (167)
| | PDF (1503 KB) | HTML

Differential evolution (DE) is one of the most powerful stochastic real parameter optimizers of current interest. In this paper, we propose a new mutation strategy, a fitness- induced parent selection scheme for the binomial crossover of DE, and a simple but effective scheme of adapting two of its most important control parameters with an objective of achieving improved performance. The new mutati... View full abstract»

• ### Exploratory Undersampling for Class-Imbalance Learning

Publication Year: 2009, Page(s):539 - 550
Cited by:  Papers (243)
| | PDF (653 KB) | HTML

Undersampling is a popular method in dealing with class-imbalance problems, which uses only a subset of the majority class and thus is very efficient. The main deficiency is that many majority class examples are ignored. We propose two algorithms to overcome this deficiency. EasyEnsemble samples several subsets from the majority class, trains a learner using each of them, and combines the outputs ... View full abstract»

• ### SVMs Modeling for Highly Imbalanced Classification

Publication Year: 2009, Page(s):281 - 288
Cited by:  Papers (193)
| | PDF (835 KB) | HTML

Traditional classification algorithms can be limited in their performance on highly unbalanced data sets. A popular stream of work for countering the problem of class imbalance has been the application of a sundry of sampling strategies. In this paper, we focus on designing modifications to support vector machines (SVMs) to appropriately tackle the problem of class imbalance. We incorporate differ... View full abstract»

• ### Reinforcement Learning Versus Model Predictive Control: A Comparison on a Power System Problem

Publication Year: 2009, Page(s):517 - 529
Cited by:  Papers (31)
| | PDF (1038 KB) | HTML

This paper compares reinforcement learning (RL) with model predictive control (MPC) in a unified framework and reports experimental results of their application to the synthesis of a controller for a nonlinear and deterministic electrical power oscillations damping problem. Both families of methods are based on the formulation of the control problem as a discrete-time optimal control problem. The ... View full abstract»

• ### Discrete-Time Nonlinear HJB Solution Using Approximate Dynamic Programming: Convergence Proof

Publication Year: 2008, Page(s):943 - 949
Cited by:  Papers (332)
| | PDF (233 KB) | HTML

Convergence of the value-iteration-based heuristic dynamic programming (HDP) algorithm is proven in the case of general nonlinear systems. That is, it is shown that HDP converges to the optimal control and the optimal value function that solves the Hamilton-Jacobi-Bellman equation appearing in infinite-horizon discrete-time (DT) nonlinear optimal control. It is assumed that, at each iteration, the... View full abstract»

• ### A DSC Approach to Robust Adaptive NN Tracking Control for Strict-Feedback Nonlinear Systems

Publication Year: 2010, Page(s):915 - 927
Cited by:  Papers (208)
| | PDF (799 KB) | HTML

A robust adaptive tracking control approach is presented for a class of strict-feedback single-input-single-output nonlinear systems. By employing radial-basis-function neural networks to account for system uncertainties, the proposed scheme is developed by combining ??dynamic surface control?? and ??minimal learning parameter?? techniques. The key features of the algorithm are that, first, the pr... View full abstract»

• ### Evolutionary algorithm based offline/online path planner for UAV navigation

Publication Year: 2003, Page(s):898 - 912
Cited by:  Papers (161)  |  Patents (1)
| | PDF (2343 KB) | HTML

An evolutionary algorithm based framework, a combination of modified breeder genetic algorithms incorporating characteristics of classic genetic algorithms, is utilized to design an offline/online path planner for unmanned aerial vehicles (UAVs) autonomous navigation. The path planner calculates a curved path line with desired characteristics in a three-dimensional (3-D) rough terrain environment,... View full abstract»

• ### A Self-Learning Particle Swarm Optimizer for Global Optimization Problems

Publication Year: 2012, Page(s):627 - 646
Cited by:  Papers (96)
| | PDF (832 KB) | HTML

Particle swarm optimization (PSO) has been shown as an effective tool for solving global optimization problems. So far, most PSO algorithms use a single learning pattern for all particles, which means that all particles in a swarm use the same strategy. This monotonic learning pattern may cause the lack of intelligence for a particular particle, which makes it unable to deal with different complex... View full abstract»

• ### Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure

Publication Year: 2004, Page(s):1907 - 1916
Cited by:  Papers (370)
| | PDF (755 KB) | HTML

Fuzzy c-means clustering (FCM) with spatial constraints (FCM_S) is an effective algorithm suitable for image segmentation. Its effectiveness contributes not only to the introduction of fuzziness for belongingness of each pixel but also to exploitation of spatial contextual information. Although the contextual information can raise its insensitivity to noise to some extent, FCM_S still la... View full abstract»

• ### L1-Norm-Based 2DPCA

Publication Year: 2010, Page(s):1170 - 1175
Cited by:  Papers (62)
| | PDF (489 KB) | HTML

In this paper, we first present a simple but effective L1-norm-based two-dimensional principal component analysis (2DPCA). Traditional L2-norm-based least squares criterion is sensitive to outliers, while the newly proposed L1-norm 2DPCA is robust. Experimental results demonstrate its advantages. View full abstract»

• ### Finite-Time Attitude Tracking Control for Spacecraft Using Terminal Sliding Mode and Chebyshev Neural Network

Publication Year: 2011, Page(s):950 - 963
Cited by:  Papers (115)
| | PDF (360 KB) | HTML

A finite-time attitude tracking control scheme is proposed for spacecraft using terminal sliding mode and Chebyshev neural network (NN) (CNN). The four-parameter representations (quaternion) are used to describe the spacecraft attitude for global representation without singularities. The attitude state (i.e., attitude and velocity) error dynamics is transformed to a double integrator dynamics with... View full abstract»

• ### On Learning, Representing, and Generalizing a Task in a Humanoid Robot

Publication Year: 2007, Page(s):286 - 298
Cited by:  Papers (350)
| | PDF (1110 KB) | HTML

We present a programming-by-demonstration framework for generically extracting the relevant features of a given task and for addressing the problem of generalizing the acquired knowledge to different contexts. We validate the architecture through a series of experiments, in which a human demonstrator teaches a humanoid robot simple manipulatory tasks. A probability-based estimation of the relevanc... View full abstract»

• ### Multiview Spectral Embedding

Publication Year: 2010, Page(s):1438 - 1446
Cited by:  Papers (140)
| | PDF (863 KB) | HTML

In computer vision and multimedia search, it is common to use multiple features from different views to represent an object. For example, to well characterize a natural scene image, it is essential to find a set of visual features to represent its color, texture, and shape information and encode each feature into a vector. Therefore, we have a set of vectors in different spaces to represent the im... View full abstract»

• ### Fractional Fuzzy Adaptive Sliding-Mode Control of a 2-DOF Direct-Drive Robot Arm

Publication Year: 2008, Page(s):1561 - 1570
Cited by:  Papers (78)
| | PDF (431 KB) | HTML

This paper presents a novel parameter adjustment scheme to improve the robustness of fuzzy sliding-mode control achieved by the use of an adaptive neuro-fuzzy inference system (ANFIS) architecture. The proposed scheme utilizes fractional-order integration in the parameter tuning stage. The controller parameters are tuned such that the system under control is driven toward the sliding regime in the... View full abstract»

• ### Robust $H_{infty}$ Control for Networked Systems With Random Packet Losses

Publication Year: 2007, Page(s):916 - 924
Cited by:  Papers (264)
| | PDF (301 KB) | HTML

In this paper, the robust Hinfin control problem Is considered for a class of networked systems with random communication packet losses. Because of the limited bandwidth of the channels, such random packet losses could occur, simultaneously, in the communication channels from the sensor to the controller and from the controller to the actuator. The random packet loss is assumed to obey the Bernoul... View full abstract»

• ### Supervised nonlinear dimensionality reduction for visualization and classification

Publication Year: 2005, Page(s):1098 - 1107
Cited by:  Papers (188)  |  Patents (2)
| | PDF (1180 KB) | HTML

When performing visualization and classification, people often confront the problem of dimensionality reduction. Isomap is one of the most promising nonlinear dimensionality reduction techniques. However, when Isomap is applied to real-world data, it shows some limitations, such as being sensitive to noise. In this paper, an improved version of Isomap, namely S-Isomap, is proposed. S-Isomap utiliz... View full abstract»

• ### Adaptive NN Backstepping Output-Feedback Control for Stochastic Nonlinear Strict-Feedback Systems With Time-Varying Delays

Publication Year: 2010, Page(s):939 - 950
Cited by:  Papers (189)
| | PDF (282 KB) | HTML

For the first time, this paper addresses the problem of adaptive output-feedback control for a class of uncertain stochastic nonlinear strict-feedback systems with time-varying delays using neural networks (NNs). The circle criterion is applied to designing a nonlinear observer, and no linear growth condition is imposed on nonlinear functions depending on system states. Under the assumption that t... View full abstract»

• ### Adaptive Robust Motion/Force Control of Holonomic-Constrained Nonholonomic Mobile Manipulators

Publication Year: 2007, Page(s):607 - 616
Cited by:  Papers (100)
| | PDF (527 KB) | HTML

In this paper, adaptive robust force/motion control strategies are presented for mobile manipulators under both holonomic and nonholonomic constraints in the presence of uncertainties and disturbances. The proposed control is robust not only to parameter uncertainties such as mass variations but also to external ones such as disturbances. The stability of the closed-loop system and the boundedness... View full abstract»

• ### A hybrid of genetic algorithm and particle swarm optimization for recurrent network design

Publication Year: 2004, Page(s):997 - 1006
Cited by:  Papers (411)  |  Patents (1)
| | PDF (472 KB) | HTML

An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid of genetic algorithm (GA) and particle swarm optimization (PSO), and is thus called HGAPSO. In HGAPSO, individuals in a new generation are created, not only by crossover a... View full abstract»

• ### Development of a biomimetic robotic fish and its control algorithm

Publication Year: 2004, Page(s):1798 - 1810
Cited by:  Papers (198)
| | PDF (542 KB) | HTML

This paper is concerned with the design of a robotic fish and its motion control algorithms. A radio-controlled, four-link biomimetic robotic fish is developed using a flexible posterior body and an oscillating foil as a propeller. The swimming speed of the robotic fish is adjusted by modulating joint's oscillating frequency, and its orientation is tuned by different joint's deflections. Since the... View full abstract»

• ### Feature generation using genetic programming with application to fault classification

Publication Year: 2005, Page(s):89 - 99
Cited by:  Papers (82)
| | PDF (544 KB) | HTML

One of the major challenges in pattern recognition problems is the feature extraction process which derives new features from existing features, or directly from raw data in order to reduce the cost of computation during the classification process, while improving classifier efficiency. Most current feature extraction techniques transform the original pattern vector into a new vector with increase... View full abstract»

• ### Quantum Reinforcement Learning

Publication Year: 2008, Page(s):1207 - 1220
Cited by:  Papers (45)
| | PDF (1022 KB) | HTML

The key approaches for machine learning, particularly learning in unknown probabilistic environments, are new representations and computation mechanisms. In this paper, a novel quantum reinforcement learning (QRL) method is proposed by combining quantum theory and reinforcement learning (RL). Inspired by the state superposition principle and quantum parallelism, a framework of a value-updating alg... View full abstract»

• ### Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain

Publication Year: 2006, Page(s):458 - 466
Cited by:  Papers (238)
| | PDF (1617 KB) | HTML

This paper presents a novel illumination normalization approach for face recognition under varying lighting conditions. In the proposed approach, a discrete cosine transform (DCT) is employed to compensate for illumination variations in the logarithm domain. Since illumination variations mainly lie in the low-frequency band, an appropriate number of DCT coefficients are truncated to minimize varia... View full abstract»

• ### Genetic K-means algorithm

Publication Year: 1999, Page(s):433 - 439
Cited by:  Papers (344)
| | PDF (180 KB)

In this paper, we propose a novel hybrid genetic algorithm (GA) that finds a globally optimal partition of a given data into a specified number of clusters. GA's used earlier in clustering employ either an expensive crossover operator to generate valid child chromosomes from parent chromosomes or a costly fitness function or both. To circumvent these expensive operations, we hybridize GA with a cl... View full abstract»

• ### Optimal Linear-Consensus Algorithms: An LQR Perspective

Publication Year: 2010, Page(s):819 - 830
Cited by:  Papers (85)
| | PDF (307 KB) | HTML

Laplacian matrices play an important role in linear-consensus algorithms. This paper studies optimal linear-consensus algorithms for multivehicle systems with single-integrator dynamics in both continuous-time and discrete-time settings. We propose two global cost functions, namely, interaction-free and interaction-related cost functions. With the interaction-free cost function, we derive the opti... View full abstract»

• ### New Methods in Iris Recognition

Publication Year: 2007, Page(s):1167 - 1175
Cited by:  Papers (387)  |  Patents (4)
| | PDF (504 KB) | HTML

This paper presents the following four advances in iris recognition: 1) more disciplined methods for detecting and faithfully modeling the iris inner and outer boundaries with active contours, leading to more flexible embedded coordinate systems; 2) Fourier-based methods for solving problems in iris trigonometry and projective geometry, allowing off-axis gaze to be handled by detecting it and ldqu... View full abstract»

• ### Distributed Primal–Dual Subgradient Method for Multiagent Optimization via Consensus Algorithms

Publication Year: 2011, Page(s):1715 - 1724
Cited by:  Papers (56)
| | PDF (230 KB) | HTML

This paper studies the problem of optimizing the sum of multiple agents' local convex objective functions, subject to global convex inequality constraints and a convex state constraint set over a network. Through characterizing the primal and dual optimal solutions as the saddle points of the Lagrangian function associated with the problem, we propose a distributed algorithm, named the distributed... View full abstract»

• ### An Effective PSO-Based Memetic Algorithm for Flow Shop Scheduling

Publication Year: 2007, Page(s):18 - 27
Cited by:  Papers (178)
| | PDF (376 KB) | HTML

This paper proposes an effective particle swarm optimization (PSO)-based memetic algorithm (MA) for the permutation flow shop scheduling problem (PFSSP) with the objective to minimize the maximum completion time, which is a typical non-deterministic polynomial-time (NP) hard combinatorial optimization problem. In the proposed PSO-based MA (PSOMA), both PSO-based searching operators and some specia... View full abstract»

• ### Observer-Based Adaptive Fuzzy Backstepping Control for a Class of Stochastic Nonlinear Strict-Feedback Systems

Publication Year: 2011, Page(s):1693 - 1704
Cited by:  Papers (244)
| | PDF (256 KB) | HTML

In this paper, two adaptive fuzzy output feedback control approaches are proposed for a class of uncertain stochastic nonlinear strict-feedback systems without the measurements of the states. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy state observer is designed for estimating the unmeasured states. On the basis of the fuzzy state observer, and by c... View full abstract»

• ### Identification of nonlinear dynamic systems using functional link artificial neural networks

Publication Year: 1999, Page(s):254 - 262
Cited by:  Papers (176)
| | PDF (300 KB)

We have presented an alternate ANN structure called functional link ANN (FLANN) for nonlinear dynamic system identification using the popular backpropagation algorithm. In contrast to a feedforward ANN structure, i.e., a multilayer perceptron (MLP), the FLANN is basically a single layer structure in which nonlinearity is introduced by enhancing the input pattern with nonlinear functional expansion... View full abstract»

• ### Nonlinear dynamic system identification using Chebyshev functional link artificial neural networks

Publication Year: 2002, Page(s):505 - 511
Cited by:  Papers (127)
| | PDF (290 KB) | HTML

A computationally efficient artificial neural network (ANN) for the purpose of dynamic nonlinear system identification is proposed. The major drawback of feedforward neural networks, such as multilayer perceptrons (MLPs) trained with the backpropagation (BP) algorithm, is that they require a large amount of computation for learning. We propose a single-layer functional-link ANN (FLANN) in which th... View full abstract»

• ### Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients

Publication Year: 2004, Page(s):499 - 516
Cited by:  Papers (285)
| | PDF (488 KB) | HTML

In this paper, adaptive neural control is presented for a class of strict-feedback nonlinear systems with unknown time delays. The proposed design method does not require a priori knowledge of the signs of the unknown virtual control coefficients. The unknown time delays are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. It is proved that the proposed backstepping... View full abstract»

• ### Observer-Based Adaptive Fuzzy Backstepping Dynamic Surface Control for a Class of MIMO Nonlinear Systems

Publication Year: 2011, Page(s):1124 - 1135
Cited by:  Papers (156)
| | PDF (293 KB) | HTML

In this paper, an adaptive fuzzy backstepping dynamic surface control (DSC) approach is developed for a class of multiple-input-multiple-output nonlinear systems with immeasurable states. Using fuzzy-logic systems to approximate the unknown nonlinear functions, a fuzzy state observer is designed to estimate the immeasurable states. By combining adaptive-backstepping technique and DSC technique, an... View full abstract»

• ### Stabilization of Nonlinear Systems Using Sampled-Data Output-Feedback Fuzzy Controller Based on Polynomial-Fuzzy-Model-Based Control Approach

Publication Year: 2012, Page(s):258 - 267
Cited by:  Papers (52)
| | PDF (276 KB) | HTML

This paper investigates the stability of sampled-data output-feedback (SDOF) polynomial-fuzzy-model-based control systems. Representing the nonlinear plant using a polynomial fuzzy model, an SDOF fuzzy controller is proposed to perform the control process using the system output information. As only the system output is available for feedback compensation, it is more challenging for the controller... View full abstract»

• ### Cooperative Control and Potential Games

Publication Year: 2009, Page(s):1393 - 1407
Cited by:  Papers (155)
| | PDF (640 KB) | HTML

We present a view of cooperative control using the language of learning in games. We review the game-theoretic concepts of potential and weakly acyclic games, and demonstrate how several cooperative control problems, such as consensus and dynamic sensor coverage, can be formulated in these settings. Motivated by this connection, we build upon game-theoretic concepts to better accommodate a broader... View full abstract»

• ### Color Image Segmentation Based on Mean Shift and Normalized Cuts

Publication Year: 2007, Page(s):1382 - 1389
Cited by:  Papers (148)  |  Patents (3)
| | PDF (1001 KB) | HTML

In this correspondence, we develop a novel approach that provides effective and robust segmentation of color images. By incorporating the advantages of the mean shift (MS) segmentation and the normalized cut (Ncut) partitioning methods, the proposed method requires low computational complexity and is therefore very feasible for real-time image segmentation processing. It preprocesses an image by u... View full abstract»

• ### Decentralized Robust Adaptive Control for the Multiagent System Consensus Problem Using Neural Networks

Publication Year: 2009, Page(s):636 - 647
Cited by:  Papers (215)
| | PDF (913 KB) | HTML

A robust adaptive control approach is proposed to solve the consensus problem of multiagent systems. Compared with the previous work, the agent's dynamics includes the uncertainties and external disturbances, which is more practical in real-world applications. Due to the approximation capability of neural networks, the uncertain dynamics is compensated by the adaptive neural network scheme. The ef... View full abstract»

• ### Reinforcement Learning for Partially Observable Dynamic Processes: Adaptive Dynamic Programming Using Measured Output Data

Publication Year: 2011, Page(s):14 - 25
Cited by:  Papers (113)
| | PDF (473 KB) | HTML

Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured inp... View full abstract»

• ### A unified quadratic-programming-based dynamical system approach to joint torque optimization of physically constrained redundant manipulators

Publication Year: 2004, Page(s):2126 - 2132
Cited by:  Papers (105)
| | PDF (299 KB) | HTML

In this paper, for joint torque optimization of redundant manipulators subject to physical constraints, we show that velocity-level and acceleration-level redundancy-resolution schemes both can be formulated as a quadratic programming (QP) problem subject to equality and inequality/bound constraints. To solve this QP problem online, a primal-dual dynamical system solver is further presented based ... View full abstract»

• ### Design and Analysis of High-Capacity Associative Memories Based on a Class of Discrete-Time Recurrent Neural Networks

Publication Year: 2008, Page(s):1525 - 1536
Cited by:  Papers (57)
| | PDF (491 KB) | HTML

This paper presents a design method for synthesizing associative memories based on discrete-time recurrent neural networks. The proposed procedure enables both hetero- and autoassociative memories to be synthesized with high storage capacity and assured global asymptotic stability. The stored patterns are retrieved by feeding probes via external inputs rather than initial conditions. As typical re... View full abstract»

• ### Applications of Artificial Intelligence in Safe Human–Robot Interactions

Publication Year: 2011, Page(s):448 - 459
Cited by:  Papers (12)
| | PDF (1308 KB) | HTML

The integration of industrial robots into the human workspace presents a set of unique challenges. This paper introduces a new sensory system for modeling, tracking, and predicting human motions within a robot workspace. A reactive control scheme to modify a robot's operations for accommodating the presence of the human within the robot workspace is also presented. To this end, a special class of ... View full abstract»

## 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