# IEEE Transactions on Neural Networks and Learning Systems

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Displaying Results 1 - 20 of 20
• ### Table of contents

Publication Year: 2012, Page(s): C1
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• ### IEEE Transactions on Neural Networks and Learning Systems publication information

Publication Year: 2012, Page(s): C2
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• ### $L_{1/2}$Regularization: A Thresholding Representation Theory and a Fast Solver

Publication Year: 2012, Page(s):1013 - 1027
Cited by:  Papers (254)  |  Patents (1)
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The special importance of L1/2regularization has been recognized in recent studies on sparse modeling (particularly on compressed sensing). The L1/2regularization, however, leads to a nonconvex, nonsmooth, and non-Lipschitz optimization problem that is difficult to solve fast and efficiently. In this paper, through developing a threshoding representation theory for L1/2<... View full abstract»

• ### Toward Automatic Time-Series Forecasting Using Neural Networks

Publication Year: 2012, Page(s):1028 - 1039
Cited by:  Papers (47)
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Over the past few decades, application of artificial neural networks (ANN) to time-series forecasting (TSF) has been growing rapidly due to several unique features of ANN models. However, to date, a consistent ANN performance over different studies has not been achieved. Many factors contribute to the inconsistency in the performance of neural network models. One such factor is that ANN modeling i... View full abstract»

• ### Novel Cascade FPGA Accelerator for Support Vector Machines Classification

Publication Year: 2012, Page(s):1040 - 1052
Cited by:  Papers (45)
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Support vector machines (SVMs) are a powerful machine learning tool, providing state-of-the-art accuracy to many classification problems. However, SVM classification is a computationally complex task, suffering from linear dependencies on the number of the support vectors and the problem's dimensionality. This paper presents a fully scalable field programmable gate array (FPGA) architecture for th... View full abstract»

• ### Robust GRBF Static Neurocontroller With Switch Logic for Control of Robot Manipulators

Publication Year: 2012, Page(s):1053 - 1064
Cited by:  Papers (15)
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A new Gaussian radial basis function static neurocontroller is presented for stable adaptive tracking control. This is a two-stage controller acting in a supervisory fashion by means of a switch logic and allowing arbitration between a neural network (NN) and a robust proportional-derivative controller. The structure is intended to reduce the effects of the curse of dimensionality in multidimensio... View full abstract»

• ### VLSI Implementation of a Bio-Inspired Olfactory Spiking Neural Network

Publication Year: 2012, Page(s):1065 - 1073
Cited by:  Papers (22)
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This paper presents a low-power, neuromorphic spiking neural network (SNN) chip that can be integrated in an electronic nose system to classify odor. The proposed SNN takes advantage of sub-threshold oscillation and onset-latency representation to reduce power consumption and chip area, providing a more distinct output for each odor input. The synaptic weights between the mitral and cortical cells... View full abstract»

• ### Transductive Ordinal Regression

Publication Year: 2012, Page(s):1074 - 1086
Cited by:  Papers (24)
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Ordinal regression is commonly formulated as a multiclass problem with ordinal constraints. The challenge of designing accurate classifiers for ordinal regression generally increases with the number of classes involved, due to the large number of labeled patterns that are needed. The availability of ordinal class labels, however, is often costly to calibrate or difficult to obtain. Unlabeled patte... View full abstract»

• ### Online Nonnegative Matrix Factorization With Robust Stochastic Approximation

Publication Year: 2012, Page(s):1087 - 1099
Cited by:  Papers (163)
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Nonnegative matrix factorization (NMF) has become a popular dimension-reduction method and has been widely applied to image processing and pattern recognition problems. However, conventional NMF learning methods require the entire dataset to reside in the memory and thus cannot be applied to large-scale or streaming datasets. In this paper, we propose an efficient online RSA-NMF algorithm (OR-NMF)... View full abstract»

• ### SSC: A Classifier Combination Method Based on Signal Strength

Publication Year: 2012, Page(s):1100 - 1117
Cited by:  Papers (12)
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We propose a new classifier combination method, the signal strength-based combining (SSC) approach, to combine the outputs of multiple classifiers to support the decision-making process in classification tasks. As ensemble learning methods have attracted growing attention from both academia and industry recently, it is critical to understand the fundamental issues of the combining rule. Motivated ... View full abstract»

• ### Online Optimal Control of Affine Nonlinear Discrete-Time Systems With Unknown Internal Dynamics by Using Time-Based Policy Update

Publication Year: 2012, Page(s):1118 - 1129
Cited by:  Papers (149)
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In this paper, the Hamilton-Jacobi-Bellman equation is solved forward-in-time for the optimal control of a class of general affine nonlinear discrete-time systems without using value and policy iterations. The proposed approach, referred to as adaptive dynamic programming, uses two neural networks (NNs), to solve the infinite horizon optimal regulation control of affine nonlinear discrete-time sys... View full abstract»

• ### Reproducing Kernel Hilbert Space Approach for the Online Update of Radial Bases in Neuro-Adaptive Control

Publication Year: 2012, Page(s):1130 - 1141
Cited by:  Papers (27)
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Classical work in model reference adaptive control for uncertain nonlinear dynamical systems with a radial basis function (RBF) neural network adaptive element does not guarantee that the network weights stay bounded in a compact neighborhood of the ideal weights when the system signals are not persistently exciting (PE). Recent work has shown, however, that an adaptive controller using specifical... View full abstract»

• ### Simple Proof of Convergence of the SMO Algorithm for Different SVM Variants

Publication Year: 2012, Page(s):1142 - 1147
Cited by:  Papers (17)
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In this brief, we give a new proof of the asymptotic convergence of the sequential minimum optimization (SMO) algorithm for both the most violating pair and second order rules to select the pair of coefficients to be updated. The proof is more self-contained, shorter, and simpler than previous ones and has a different flavor, partially building upon Gilbert's original convergence proof of its algo... View full abstract»

• ### RBF Networks Under the Concurrent Fault Situation

Publication Year: 2012, Page(s):1148 - 1155
Cited by:  Papers (10)
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Fault tolerance is an interesting topic in neural networks. However, many existing results on this topic focus only on the situation of a single fault source. In fact, a trained network may be affected by multiple fault sources. This brief studies the performance of faulty radial basis function (RBF) networks that suffer from multiplicative weight noise and open weight fault concurrently. We deriv... View full abstract»

• ### Neural Network-Based Distributed Attitude Coordination Control for Spacecraft Formation Flying With Input Saturation

Publication Year: 2012, Page(s):1155 - 1162
Cited by:  Papers (49)
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This brief considers the attitude coordination control problem for spacecraft formation flying when only a subset of the group members has access to the common reference attitude. A quaternion-based distributed attitude coordination control scheme is proposed with consideration of the input saturation and with the aid of the sliding-mode observer, separation principle theorem, Chebyshev neural net... View full abstract»

• ### Universal Neural Network Control of MIMO Uncertain Nonlinear Systems

Publication Year: 2012, Page(s):1163 - 1169
Cited by:  Papers (15)
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In this brief, a continuous tracking control law is proposed for a class of high-order multi-input-multi-output uncertain nonlinear dynamic systems with external disturbance and unknown varying control direction matrix. The proposed controller consists of high-gain feedback, Nussbaum gain matrix selector, online approximator (OLA) model and a robust term. The OLA model is represented by a two-laye... View full abstract»

• ### Spectral Graph Optimization for Instance Reduction

Publication Year: 2012, Page(s):1169 - 1175
Cited by:  Papers (4)
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The operation of instance-based learning algorithms is based on storing a large set of prototypes in the system's database. However, such systems often experience issues with storage requirements, sensitivity to noise, and computational complexity, which result in high search and response times. In this brief, we introduce a novel framework that employs spectral graph theory to efficiently partiti... View full abstract»

• ### IJCNN 2013

Publication Year: 2012, Page(s): 1176
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• ### IEEE Computational Intelligence Society Information

Publication Year: 2012, Page(s): C3
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• ### IEEE Transactions on Neural Networks information for authors

Publication Year: 2012, Page(s): C4
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## 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.

Full Aims & Scope

## 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