Volume 25 Issue 6 • June 2014
Filter Results
-
Table of contents
Publication Year: 2014, Page(s): C1|
PDF (119 KB)
-
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS publication information
Publication Year: 2014, Page(s): C2|
PDF (140 KB)
-
A Self-Building and Cluster-Based Cognitive Fault Diagnosis System for Sensor Networks
Publication Year: 2014, Page(s):1021 - 1032
Cited by: Papers (12)Cognitive fault diagnosis systems differentiate from more traditional solutions by providing online strategies to create and update the fault-free and the faulty classes directly from incoming data. This aspect is of paramount relevance within the big data framework, since measurements are there immediately processed to detect and identify the upsurge of potential faults. This paper introduces a n... View full abstract»
-
A Simple Scheme for Formation Control Based on Weighted Behavior Learning
Publication Year: 2014, Page(s):1033 - 1044
Cited by: Papers (8)Several correlated issues of autonomy and simplicity regarding formation control for robots with a self-awareness mechanism in unstructured environments are considered. To achieve autonomy and simplicity, a hybrid scheme is derived for robot maneuvering based on a multibehavioral system. The system holds some self-awareness capabilities ensuring precision and robustness in the presence of internal... View full abstract»
-
New Criteria for Global Robust Stability of Delayed Neural Networks With Norm-Bounded Uncertainties
Publication Year: 2014, Page(s):1045 - 1052
Cited by: Papers (27)In this paper, we study the global asymptotic robust stability of delayed neural networks with norm-bounded uncertainties. By employing the Lyapunov stability theory and homeomorphic mapping theorem, we derive some new types of sufficient conditions ensuring the existence, uniqueness, and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delay... View full abstract»
-
A Nonlinear Semantic-Preserving Projection Approach to Visualize Multivariate Periodical Time Series
Publication Year: 2014, Page(s):1053 - 1070A major drawback of nonlinear dimensionality reduction (DR) techniques is their inability to preserve some authentic information from the source domain, leading to projections that are often hard to interpret when it comes to observing anything other than the topological structure of the data. In this paper, we propose a nonlinear DR approach enforcing projection constraints resulting from an a pr... View full abstract»
-
Local Coordinate Concept Factorization for Image Representation
Publication Year: 2014, Page(s):1071 - 1082
Cited by: Papers (8)Learning sparse representation of high-dimensional data is a state-of-the-art method for modeling data. Matrix factorization-based techniques, such as nonnegative matrix factorization and concept factorization (CF), have shown great advantages in this area, especially useful for image representation. Both of them are linear learning problems and lead to a sparse representation of the images. Howev... View full abstract»
-
Global and Local Structure Preservation for Feature Selection
Publication Year: 2014, Page(s):1083 - 1095
Cited by: Papers (20)The recent literature indicates that preserving global pairwise sample similarity is of great importance for feature selection and that many existing selection criteria essentially work in this way. In this paper, we argue that besides global pairwise sample similarity, the local geometric structure of data is also critical and that these two factors play different roles in different learning scen... View full abstract»
-
A Load-Balancing Self-Organizing Incremental Neural Network
Publication Year: 2014, Page(s):1096 - 1105
Cited by: Papers (6)Clustering is widely used in machine learning, feature extraction, pattern recognition, image analysis, information retrieval, and bioinformatics. Online unsupervised incremental learning is an important branch of data clustering. However, accurately separating high-density overlapped areas in a network has a direct impact on the performance of the clustering algorithm. In this paper, we propose a... View full abstract»
-
Optimal Switching and Control of Nonlinear Switching Systems Using Approximate Dynamic Programming
Publication Year: 2014, Page(s):1106 - 1117
Cited by: Papers (13)The problem of optimal switching and control of switching systems with nonlinear subsystems is investigated in this paper. An approximate dynamic programming-based algorithm is proposed for learning the optimal cost-to-go function based on the switching instants and the initial conditions. The global optimal switching times for every selected initial condition are directly found through the minimi... View full abstract»
-
Nonconvex Regularizations for Feature Selection in Ranking With Sparse SVM
Publication Year: 2014, Page(s):1118 - 1130
Cited by: Papers (21)Feature selection in learning to rank has recently emerged as a crucial issue. Whereas several preprocessing approaches have been proposed, only a few have focused on integrating feature selection into the learning process. In this paper, we propose a general framework for feature selection in learning to rank using support vector machines with a sparse regularization term. We investigate both cla... View full abstract»
-
Multiset Canonical Correlations Using Globality Preserving Projections With Applications to Feature Extraction and Recognition
Publication Year: 2014, Page(s):1131 - 1146
Cited by: Papers (9)Multiset features extracted from the same patterns always represent different characteristics of data. Thus, it is very valuable to perform the extraction on multiple feature sets. This paper addresses the issue of multiset correlation feature extraction (MCFE) in multiple feature representations. A novel method is proposed to carry out the MCFE for classification, called multiset canonical correl... View full abstract»
-
Efficient Exploratory Learning of Inverse Kinematics on a Bionic Elephant Trunk
Publication Year: 2014, Page(s):1147 - 1160
Cited by: Papers (25)We present an approach to learn the inverse kinematics of the “bionic handling assistant”-an elephant trunk robot. This task comprises substantial challenges including high dimensionality, restrictive and unknown actuation ranges, and nonstationary system behavior. We use a recent exploration scheme, online goal babbling, which deals with these challenges by bootstrapping and adaptin... View full abstract»
-
Novel LMI-Based Condition on Global Asymptotic Stability for a Class of Cohen–Grossberg BAM Networks With Extended Activation Functions
Publication Year: 2014, Page(s):1161 - 1172
Cited by: Papers (20)This paper is concerned with global asymptotic stability of a class of Cohen-Grossberg bidirectional associative memory (BAM) neural networks with delays. Under the assumptions that the activation functions only satisfy the so-called extended global Lipschitz condition and the behaved functions only satisfy global Lipschitz condition, we apply linear matrix inequality (LMI) method and homeomorphis... View full abstract»
-
Semisupervised Classification Through the Bag-of-Paths Group Betweenness
Publication Year: 2014, Page(s):1173 - 1186
Cited by: Papers (5)This paper introduces a novel and well-founded betweenness measure, called the bag-of-paths (BoP) betweenness, as well as its extension, the BoP group betweenness, to tackle semisupervised classification problems on weighted directed graphs. The objective of semisupervised classification is to assign a label to unlabeled nodes using the whole topology of the graph and the labeled nodes at our disp... View full abstract»
-
Rapid Oscillation Fault Detection and Isolation for Distributed Systems via Deterministic Learning
Publication Year: 2014, Page(s):1187 - 1199
Cited by: Papers (4)In this paper, a rapid detection and isolation scheme for oscillation faults in a distributed nonlinear system is proposed. The distributed nonlinear system considered is modeled as a set of interconnected subsystems. First, a local learning and merging method based on deterministic learning theory is proposed to obtain knowledge of the unknown interconnections and the fault functions. Second, usi... View full abstract»
-
Gaussian Classifier-Based Evolutionary Strategy for Multimodal Optimization
Publication Year: 2014, Page(s):1200 - 1216
Cited by: Papers (28)This paper presents a Gaussian classifier-based evolutionary strategy (GCES) to solve multimodal optimization problems. An evolutionary technique for them must answer two crucial questions to guarantee its success: how to distinguish among the different basins of attraction and how to safeguard the already discovered good-quality solutions including both global and local optima. In GCES, multimoda... View full abstract»
-
Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks
Publication Year: 2014, Page(s):1217 - 1226
Cited by: Papers (126)Because of the complexity of consensus control of nonlinear multiagent systems in state time-delay, most of previous works focused only on linear systems with input time-delay. An adaptive neural network (NN) consensus control method for a class of nonlinear multiagent systems with state time-delay is proposed in this paper. The approximation property of radial basis function neural networks (RBFN... View full abstract»
-
Open Access
Publication Year: 2014, Page(s): 1227|
PDF (1156 KB)
-
2014 IEEE Symposium Series on Computational Intelligience
Publication Year: 2014, Page(s): 1228|
PDF (2167 KB)
-
IEEE Computational Intelligence Society Information
Publication Year: 2014, Page(s): C3|
PDF (125 KB)
-
IEEE Transactions on Neural Networks information for authors
Publication Year: 2014, Page(s): C4|
PDF (128 KB)
Aims & Scope
IEEE Transactions on Neural Networks and Learning Systems publishes technical articles that deal with the theory, design, and applications of neural networks and related learning systems.
Meet Our Editors
Editor-in-Chief
Haibo He
Dept. of Electrical, Computer, and Biomedical Engineering
University of Rhode Island
Kingston, RI 02881, USA
ieeetnnls@gmail.com