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

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Displaying Results 1 - 25 of 29

Publication Year: 2010, Page(s): C1
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• ### IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics publication information

Publication Year: 2010, Page(s): C2
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• ### Editorial

Publication Year: 2010, Page(s): 1
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• ### Adaptive and Learning Systems

Publication Year: 2010, Page(s):2 - 5
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• ### Solving Multiconstraint Assignment Problems Using Learning Automata

Publication Year: 2010, Page(s):6 - 18
Cited by:  Papers (22)
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This paper considers the NP-hard problem of object assignment with respect to multiple constraints: assigning a set of elements (or objects) into mutually exclusive classes (or groups), where the elements which are ldquosimilarrdquo to each other are hopefully located in the same class. The literature reports solutions in which the similarity constraint consists of a single in... View full abstract»

• ### A Team of Continuous-Action Learning Automata for Noise-Tolerant Learning of Half-Spaces

Publication Year: 2010, Page(s):19 - 28
Cited by:  Papers (20)
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Learning automata are adaptive decision making devices that are found useful in a variety of machine learning and pattern recognition applications. Although most learning automata methods deal with the case of finitely many actions for the automaton, there are also models of continuous-action-set learning automata (CALA). A team of such CALA can be useful in stochastic optimization problems where ... View full abstract»

• ### Modeling a Student–Classroom Interaction in a Tutorial-Like System Using Learning Automata

Publication Year: 2010, Page(s):29 - 42
Cited by:  Papers (21)
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Almost all of the learning paradigms used in machine learning, learning automata (LA), and learning theory, in general, use the philosophy of a student (learning mechanism) attempting to learn from a teacher. This paradigm has been generalized in a myriad of ways, including the scenario when there are multiple teachers or a hierarchy of mechanisms that collectively achieve the learning. In this pa... View full abstract»

• ### Standalone CMAC Control System With Online Learning Ability

Publication Year: 2010, Page(s):43 - 53
Cited by:  Papers (19)
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A cerebellar model articulation controller (CMAC) control system, which contains only one single-input controller implemented by a differentiable CMAC, is proposed in this paper. In the proposed scheme, the CMAC controller is solely used to control the plant, and no conventional controller is needed. Without a preliminary offline learning, the single-input CMAC controller can provide the control e... View full abstract»

• ### Cellular Learning Automata With Multiple Learning Automata in Each Cell and Its Applications

Publication Year: 2010, Page(s):54 - 65
Cited by:  Papers (42)
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The cellular learning automaton (CLA), which is a combination of cellular automaton (CA) and learning automaton (LA), is introduced recently. This model is superior to CA because of its ability to learn and is also superior to single LA because it is a collection of LAs which can interact with each other. The basic idea of CLA is to use LA to adjust the state transition probability of stochastic C... View full abstract»

• ### Random Early Detection for Congestion Avoidance in Wired Networks: A Discretized Pursuit Learning-Automata-Like Solution

Publication Year: 2010, Page(s):66 - 76
Cited by:  Papers (45)
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In this paper, we present a learning-automata-like (LAL) mechanism for congestion avoidance in wired networks. Our algorithm, named as LAL random early detection (LALRED), is founded on the principles of the operations of existing RED congestion-avoidance mechanisms, augmented with a LAL philosophy. The primary objective of LALRED is to optimize the value of the average size of the queue used for ... View full abstract»

• ### Biomimetic Approach to Tacit Learning Based on Compound Control

Publication Year: 2010, Page(s):77 - 90
Cited by:  Papers (11)
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The remarkable capability of living organisms to adapt to unknown environments is due to learning mechanisms that are totally different from the current artificial machine-learning paradigm. Computational media composed of identical elements that have simple activity rules play a major role in biological control, such as the activities of neurons in brains and the molecular interactions in intrace... View full abstract»

• ### Development of Quantum-Based Adaptive Neuro-Fuzzy Networks

Publication Year: 2010, Page(s):91 - 100
Cited by:  Papers (19)
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In this study, we are concerned with a method for constructing quantum-based adaptive neuro-fuzzy networks (QANFNs) with a Takagi-Sugeno-Kang (TSK) fuzzy type based on the fuzzy granulation from a given input-output data set. For this purpose, we developed a systematic approach in producing automatic fuzzy rules based on fuzzy subtractive quantum clustering. This clustering technique is not only a... View full abstract»

• ### Can You See Me Now? Sensor Positioning for Automated and Persistent Surveillance

Publication Year: 2010, Page(s):101 - 115
Cited by:  Papers (32)
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Most existing camera placement algorithms focus on coverage and/or visibility analysis, which ensures that the object of interest is visible in the camera's field of view (FOV). However, visibility, which is a fundamental requirement of object tracking, is insufficient for automated persistent surveillance. In such applications, a continuous consistently labeled trajectory of the same object shoul... View full abstract»

• ### Set-Membership Fuzzy Filtering for Nonlinear Discrete-Time Systems

Publication Year: 2010, Page(s):116 - 124
Cited by:  Papers (24)
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This paper is concerned with the set-membership filtering (SMF) problem for discrete-time nonlinear systems. We employ the Takagi-Sugeno (T-S) fuzzy model to approximate the nonlinear systems over the true value of state and to overcome the difficulty with the linearization over a state estimate set rather than a state estimate point in the set-membership framework. Based on the T-S fuzzy model, w... View full abstract»

• ### Improving POMDP Tractability via Belief Compression and Clustering

Publication Year: 2010, Page(s):125 - 136
Cited by:  Papers (2)
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Partially observable Markov decision process (POMDP) is a commonly adopted mathematical framework for solving planning problems in stochastic environments. However, computing the optimal policy of POMDP for large-scale problems is known to be intractable, where the high dimensionality of the underlying belief space is one of the major causes. In this paper, we propose a hybrid approach that integr... View full abstract»

• ### Selecting Discrete and Continuous Features Based on Neighborhood Decision Error Minimization

Publication Year: 2010, Page(s):137 - 150
Cited by:  Papers (65)
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Feature selection plays an important role in pattern recognition and machine learning. Feature evaluation and classification complexity estimation arise as key issues in the construction of selection algorithms. To estimate classification complexity in different feature subspaces, a novel feature evaluation measure, called the neighborhood decision error rate (NDER), is proposed, which is applicab... View full abstract»

• ### Cyclorotation Models for Eyes and Cameras

Publication Year: 2010, Page(s):151 - 161
Cited by:  Papers (4)
| | PDF (639 KB) | HTML

The human visual system obeys Listing's law, which means that the cyclorotation of the eye (around the line of sight) can be predicted from the direction of the fixation point. It is shown here that Listing's law can conveniently be formulated in terms of rotation matrices. The function that defines the observed cyclorotation is derived in this representation. Two polynomial approximations of the ... View full abstract»

• ### Pipelined Chebyshev Functional Link Artificial Recurrent Neural Network for Nonlinear Adaptive Filter

Publication Year: 2010, Page(s):162 - 172
Cited by:  Papers (15)
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A novel nonlinear adaptive filter with pipelined Chebyshev functional link artificial recurrent neural network (PCFLARNN) is presented in this paper, which uses a modification real-time recurrent learning algorithm. The PCFLARNN consists of a number of simple small-scale Chebyshev functional link artificial recurrent neural network (CFLARNN) modules. Compared to the standard recurrent neural netwo... View full abstract»

• ### New Delay-Dependent Exponential $H_{infty}$ Synchronization for Uncertain Neural Networks With Mixed Time Delays

Publication Year: 2010, Page(s):173 - 185
Cited by:  Papers (233)
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This paper establishes an exponential H infin synchronization method for a class of uncertain master and slave neural networks (MSNNs) with mixed time delays, where the mixed delays comprise different neutral, discrete, and distributed time delays. The polytopic and the norm-bounded uncertainties are separately taken into consideration. An appropriate discretized Lyapunov-Krasovs... View full abstract»

• ### Generalized Discriminant Analysis: A Matrix Exponential Approach

Publication Year: 2010, Page(s):186 - 197
Cited by:  Papers (39)
| | PDF (1041 KB) | HTML

Linear discriminant analysis (LDA) is well known as a powerful tool for discriminant analysis. In the case of a small training data set, however, it cannot directly be applied to high-dimensional data. This case is the so-called small-sample-size or undersampled problem. In this paper, we propose an exponential discriminant analysis (EDA) technique to overcome the undersampled problem. The advanta... View full abstract»

• ### On Utilizing Association and Interaction Concepts for Enhancing Microaggregation in Secure Statistical Databases

Publication Year: 2010, Page(s):198 - 207
Cited by:  Papers (2)
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This paper presents a possibly pioneering endeavor to tackle the microaggregation techniques (MATs) in secure statistical databases by resorting to the principles of associative neural networks (NNs). The prior art has improved the available solutions to the MAT by incorporating proximity information, and this approach is done by recursively reducing the size of the data set by excluding points th... View full abstract»

• ### Distance Approximating Dimension Reduction of Riemannian Manifolds

Publication Year: 2010, Page(s):208 - 217
Cited by:  Papers (19)
| | PDF (800 KB) | HTML

We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geodesic distances between data points on the Riemannian manifold while preserving discrimination ability. Existing algorithms, e.g., ISOMAP, that try to learn an isometric embedding of data points on a manifold have a non-... View full abstract»

• ### Vaccine-Enhanced Artificial Immune System for Multimodal Function Optimization

Publication Year: 2010, Page(s):218 - 228
Cited by:  Papers (40)
| | PDF (1067 KB) | HTML

This paper emulates a biological notion in vaccines to promote exploration in the search space for solving multimodal function optimization problems using artificial immune systems (AISs). In this method, we first divide the decision space into equal subspaces. The vaccine is then randomly extracted from each subspace. A few of these vaccines, in the form of weakened antigens, are then injected in... View full abstract»

• ### A Multiagent Evolutionary Algorithm for Combinatorial Optimization Problems

Publication Year: 2010, Page(s):229 - 240
Cited by:  Papers (23)
| | PDF (471 KB) | HTML

Based on our previous works, multiagent systems and evolutionary algorithms (EAs) are integrated to form a new algorithm for combinatorial optimization problems (CmOPs), namely, MultiAgent EA for CmOPs (MAEA-CmOPs). In MAEA-CmOPs, all agents live in a latticelike environment, with each agent fixed on a lattice point. To increase energies, all agents compete with their neighbors, and they can also ... View full abstract»

• ### Adaptive Fuzzy Switched Swing-Up and Sliding Control for the Double-Pendulum-and-Cart System

Publication Year: 2010, Page(s):241 - 252
Cited by:  Papers (16)
| | PDF (991 KB) | HTML

In this paper, an adaptive fuzzy switched swing-up and sliding controller (AFSSSC) is proposed for the swing-up and position controls of a double-pendulum-and-cart system. The proposed AFSSSC consists of a fuzzy switching controller (FSC), an adaptive fuzzy swing-up controller (FSUC), and an adaptive hybrid fuzzy sliding controller (HFSC). To simplify the design of the adaptive HFSC, the double-pe... 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 Transactions 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