Thursday 4 December 2014

Neural Networks Voume 61, Pages 1-118, January 2015

1. Neural Networks Referees in 2014
Pages: xi-xiii

2. Exciting Time for Neural Networks  
Pages: xv-xvi
Author(s): Kenji Doya, DeLiang Wang


NEURAL NETWORKS LETTERS

3. Dynamic analysis of periodic solution for high-order discrete-time Cohen–Grossberg neural networks with time delays  
Pages: 68-74
Author(s): Kaiyun Sun, Ancai Zhang, Jianlong Qiu, Xiangyong Chen, Chengdong Yang, Xiao Chen


REVIEWS

4. Trends in extreme learning machines: A review
Pages: 32-48
Author(s): Gao Huang, Guang-Bin Huang, Shiji Song, Keyou You

5. Deep learning in neural networks: An overview
Pages: 85-117
Author(s): Jürgen Schmidhuber


LEARNING SYSTEMS

6. An efficient sampling algorithm with adaptations for Bayesian variable selection
Pages: 22-31
Author(s): Takamitsu Araki, Kazushi Ikeda, Shotaro Akaho

7. A complex-valued neural dynamical optimization approach and its stability analysis
Pages: 59-67
Author(s): Songchuan Zhang, Youshen Xia, Weixing Zheng

8. Max–min distance nonnegative matrix factorization  
Pages: 75-84
Author(s): Jim Jing-Yan Wang, Xin Gao

MATHEMATICAL AND COMPUTATIONAL ANALYSIS

9. New synchronization criteria for memristor-based networks: Adaptive control and feedback control schemes
Pages: 1-9
Author(s): Ning Li, Jinde Cao

10. A one-layer recurrent neural network for constrained nonconvex optimization
Pages: 10-21
Author(s): Guocheng Li, Zheng Yan, Jun Wang

11. Passivity analysis for memristor-based recurrent neural networks with discrete and distributed delays
Pages: 49-58
Author(s): Guodong Zhang, Yi Shen, Quan Yin, Junwei Sun

Monday 27 October 2014

Neural Networks Volume 60, Pages: 1-246, December 2014

Cognitive Science

1. How active perception and attractor dynamics shape perceptual categorization: A computational model  
Author(s): Nicola Catenacci Volpi, Jean Charles Quinton, Giovanni Pezzulo
Pages: 1-16

2. Connectionist interpretation of the association between cognitive dissonance and attention switching  
Author(s): Takao Matsumoto
Pages: 119-132

3. Neurocomputational approaches to modelling multisensory integration in the brain: A review  
Author(s): Mauro Ursino, Cristiano Cuppini, Elisa Magosso
Pages: 141-165

4. Person-by-person prediction of intuitive economic choice  
Author(s): George Mengov
Pages: 232-245


Neuroscience

5. Global exponential almost periodicity of a delayed memristor-based neural networks  
Author(s): Jiejie Chen, Zhigang Zeng, Ping Jiang
Pages: 33-43

6. Global robust asymptotic stability of variable-time impulsive BAM neural networks  
Author(s): Mustafa Şaylı, Enes Yılmaz
Pages: 67-73

7. Noise cancellation of memristive neural networks  
Author(s): Shiping Wen, Zhigang Zeng, Tingwen Huang, Xinghuo Yu
Pages: 74-83

8. Stability and bifurcation analysis of new coupled repressilators in genetic regulatory networks with delays  
Author(s): Guang Ling, Zhi-Hong Guan, Ding-Xin He, Rui-Quan Liao, Xian-He Zhang
Pages: 222-231


Learning Systems

9. Simple randomized algorithms for online learning with kernels  
Author(s): Wenwu He, James T. Kwok
Pages: 17-24

10. New approximation method for smooth error backpropagation in a quantron network  
Author(s): Simon de Montigny
Pages: 84-95

11. Unsupervised learnable neuron model with nonlinear interaction on dendrites  
Pages: 96-103
Author(s): Yuki Todo, Hiroki Tamura, Kazuya Yamashita, Zheng Tang

12. A convolutional recursive modified Self Organizing Map for handwritten digits recognition  
Author(s): Ehsan Mohebi, Adil Bagirov
Pages: 104-118

13. Logarithmic learning for generalized classifier neural network  
Author(s): Buse Melis Ozyildirim, Mutlu Avci
Pages: 133-140

14. Design of hybrid radial basis function neural networks (HRBFNNs) realized with the aid of hybridization of fuzzy clustering method (FCM) and polynomial neural networks (PNNs)  
Author(s): Wei Huang, Sung-Kwun Oh, Witold Pedrycz
Pages: 166-181

15. On extending the complex FastICA algorithms to noisy data  
Author(s): Zongli Ruan, Liping Li, Guobing Qian
Pages: 194-202

16. Online computing of non-stationary distributions velocity fields by an accuracy controlled growing neural gas  
Author(s): Hervé Frezza-Buet
Pages: 203-221


Mathematical and Computational Analysis

17. Impulsive exponential synchronization of randomly coupled neural networks with Markovian jumping and mixed model-dependent time delays  
Author(s): Xin Wang, Chuandong Li, Tingwen Huang, Ling Chen
Pages: 25-32

18. Continuous neural identifier for uncertain nonlinear systems with time delays in the input signal  
Author(s): M. Alfaro-Ponce, A. Argüelles, I. Chairez
Pages: 53-66


Engineering and Applications

19. Dynamic neural network-based robust observers for uncertain nonlinear systems  
Author(s): H.T. Dinh, R. Kamalapurkar, S. Bhasin, W.E. Dixon
Pages: 44-52

20. A computer vision system for rapid search inspired by surface-based attention mechanisms from human perception  
Author(s): Johannes Mohr, Jong-Han Park, Klaus Obermayer
Pages: 182-193

Saturday 13 September 2014

Neural Networks Special Issue: Neural Network Learning in Big Data

Big data is much more than storage of and access to data. Analytics plays an important role in making sense of that data and exploiting its value. But learning from big data has become a significant challenge and requires development of new types of algorithms. Most machine learning algorithms encounter theoretical challenges in scaling up to big data. Plus there are challenges of high dimensionality, velocity and variety for all types of machine learning algorithms. The neural network field has historically focused on algorithms that learn in an online, incremental mode without requiring in-memory access to huge amounts of data. The brain is arguably the best and most elegant big data processor and is the inspiration for neural network learning methods. Neural network type of learning is not only ideal for streaming data (as in the Industrial Internet or the Internet of Things), but could also be used for stored big data. For stored big data, neural network algorithms can learn from all of the data instead of from samples of the data. And the same is true for streaming data where not all of the data is actually stored. In general, online, incremental learning algorithms are less vulnerable to size of the data. Neural network algorithms, in particular, can take advantage of massively parallel (brain-like) computations, which use very simple processors, that other machine learning technologies cannot. Specialized neuromorphic hardware, originally meant for large-scale brain simulations, is becoming available to implement these algorithms in a massively parallel fashion. Neural network algorithms, therefore, can deliver very fast and efficient real-time learning through the use of hardware and this could be particularly useful for streaming data in the Industrial Internet. Neural network technologies thus can become significant components of big data analytics platforms and this special issue will begin that journey with big data.

For this special issue of Neural Networks, we invite papers that address many of the challenges of learning from big data. In particular, we are interested in papers on efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms), implementations on different computing platforms (e.g. neuromorphic, GPUs, clouds, clusters) and applications of online learning to solve real-world big data problems (e.g. health care, transportation, and electric power and energy management).

RECOMMENDED TOPICS:

Topics of interest include, but are not limited to:
  1. Autonomous, online, incremental learning – theory, algorithms and applications in big data
  2. High dimensional data, feature selection, feature transformation – theory, algorithms and applications for big data
  3. Scalable neural network algorithms for big data
  4. Neural network learning algorithms for high-velocity streaming data
  5. Deep neural network learning
  6. Neuromorphic hardware for scalable neural network learning
  7. Big data analytics using neural networks in healthcare/medical applications
  8. Big data analytics using neural networks in electric power and energy systems
  9. Big data analytics using neural networks in large sensor networks
  10. Big data and neural network learning in computational biology and bioinformatics

SUBMISSION PROCEDURE:

Prospective authors should visit http://ees.elsevier.com/neunet/ for information on paper submission. During the submission process, there will be steps to designate the submission to this special issue. However, please indicate on the first page of the manuscript that the manuscript is intended for the Special Issue: Neural Network Learning in Big Data. Manuscripts will be peer reviewed according to Neural Networks guidelines.

Manuscript submission due: December 15, 2014
First review completed: March 1, 2015
Revised manuscript due: April 1, 2015
Second review completed, final decisions to authors: April 15, 2015
Final manuscript due: April 30, 2015

GUEST EDITORS:

Monday 18 August 2014

Neural Networks Volume 58, Pages 1-148, October 2014

Special Issue on Affective Neural Networks and Cognitive Learning Systems for Big Data Analysis
Edited by Amir Hussain, Erik Cambria, Björn Schuller and Newton Howard

1. Affective neural networks and cognitive learning systems for big data analysis  
Pages: 1-3
Author(s): Amir Hussain, Erik Cambria, Björn Schuller, Newton Howard
   
2. Discrete particle swarm optimization for identifying community structures in signed social networks
Pages: 4-13
Author(s): Qing Cai, Maoguo Gong, Bo Shen, Lijia Ma, Licheng Jiao
   
3. An incremental community detection method for social tagging systems using locality-sensitive hashing
Pages: 14-28
Author(s): Zhenyu Wu, Ming Zou
   
4. Affective topic model for social emotion detection
Pages: 29-37
Author(s): Yanghui Rao, Qing Li, Liu Wenyin, Qingyuan Wu, Xiaojun Quan
   
5. Modeling virtual organizations with Latent Dirichlet Allocation: A case for natural language processing
Pages: 38-49
Author(s): Alexander Gross, Dhiraj Murthy
   
6. Semi-supervised word polarity identification in resource-lean languages
Pages: 50-59
Author(s): Iman Dehdarbehbahani, Azadeh Shakery, Heshaam Faili
   
7. Incorporating conditional random fields and active learning to improve sentiment identification
Pages: 60-67
Author(s): Kunpeng Zhang, Yusheng Xie, Yi Yang, Aaron Sun, Hengchang Liu, Alok Choudhary
   
8. A classification of user-generated content into consumer decision journey stages
Pages: 68-81
Author(s): Silvia Vázquez, Óscar Muñoz-García, Inés Campanella, Marc Poch, Beatriz Fisas, Nuria Bel, Gloria Andreu
   
9. Sentiments analysis at conceptual level making use of the Narrative Knowledge Representation Language
Pages: 82-97
Author(s): Gian Piero Zarri
   
10. Exploring personalized searches using tag-based user profiles and resource profiles in folksonomy
Pages: 98-110
Author(s): Yi Cai, Qing Li, Haoran Xie, Huaqin Min
   
11. Community-aware user profile enrichment in folksonomy
Pages: 111-121
Author(s): Haoran Xie, Qing Li, Xudong Mao, Xiaodong Li, Yi Cai, Yanghui Rao
   
12. A multi-label, semi-supervised classification approach applied to personality prediction in social media
Pages: 122-130
Author(s): Ana Carolina E.S. Lima, Leandro Nunes de Castro
   
13. Semantically-based priors and nuanced knowledge core for Big Data, Social AI, and language understanding
Pages: 131-147
Author(s): Daniel Olsher

Monday 28 July 2014

Neural Networks Volume 57, Pages 1-166, September 2014

Neuroscience

1. Bayesian common spatial patterns for multi-subject EEG classification
Author(s): Hyohyeong Kang, Seungjin Choi
Pages: 39-50
  
2. Estimating the correlation between bursty spike trains and local field potentials
Author(s): Zhaohui Li, Gaoxiang Ouyang, Li Yao, Xiaoli Li
Pages: 63-72

3. Effect of hybrid circle reservoir injected with wavelet-neurons on performance of echo state network
Author(s): Hongyan Cui, Chen Feng, Yuan Chai, Ren Ping Liu, Yunjie Liu
Pages: 141-151

Learning Systems

4. Noise model based image -support vector regression with its application to short-term wind speed forecasting
Author(s): Qinghua Hu, Shiguang Zhang, Zongxia Xie, Jusheng Mi, Jie Wan
Pages: 1-11
   
5. Using financial risk measures for analyzing generalization performance of machine learning models
Author(s): Akiko Takeda, Takafumi Kanamori
Pages: 29-38
   
6. Fast Gaussian kernel learning for classification tasks based on specially structured global optimization
Author(s): Shangping Zhong, Tianshun Chen, Fengying He, Yuzhen Niu
Pages: 51-62
   
7. Semi-supervised information-maximization clustering
Author(s): Daniele Calandriello, Gang Niu, Masashi Sugiyama
Pages: 103-111
   
8. Model-based policy gradients with parameter-based exploration by least-squares conditional density estimation
Author(s): Voot Tangkaratt, Syogo Mori, Tingting Zhao, Jun Morimoto, Masashi Sugiyama
Pages: 128-140

Mathematical and Computational Analysis

9. Periodicity and dissipativity for memristor-based mixed time-varying delayed neural networks via differential inclusions
Author(s): Lian Duan, Lihong Huang
Pages: 12-22
   
10. Comparing fixed and variable-width Gaussian networks
Author(s): Věra Kůrková, Paul C. Kainen
Pages: 23-28
   
11. Synchronization of memristor-based recurrent neural networks with two delay components based on second-order reciprocally convex approach
Author(s): A. Chandrasekar, R. Rakkiyappan, Jinde Cao, S. Lakshmanan
Pages: 79-93
   
12. Sudoku associative memory
Author(s): Jiann-Ming Wu, Pei-Hsun Hsu, Cheng-Yuan Liou
Pages: 112-127

Engineering and Applications

13. Neural network for solving Nash equilibrium problem in application of multiuser power control
Author(s): Xing He, Junzhi Yu, Tingwen Huang, Chuandong Li, Chaojie Li
Pages: 73-78
   
14. A new switching design to finite-time stabilization of nonlinear systems with applications to neural networks
Author(s): Xiaoyang Liu, Daniel W.C. Ho, Wenwu Yu, Jinde Cao
Pages: 94-102
   
15. Image denoising using nonsubsampled shearlet transform and twin support vector machines
Author(s): Hong-Ying Yang, Xiang-Yang Wang, Pan-Pan Niu, Yang-Cheng Liu
Pages: 152-165

Sunday 22 June 2014

Neural Networks Volume 56, Pages 1-68, August 2014

1. A global coupling index of multivariate neural series with application to the evaluation of mild cognitive impairment
Pages: 1-9
Author(s): Dong Wen, Qing Xue, Chengbiao Lu, Xinyong Guan, Yuping Wang, Xiaoli Li

2. Relative entropy minimizing noisy non-linear neural network to approximate stochastic processes
Pages: 10-21
Author(s): Mathieu N. Galtier, Camille Marini, Gilles Wainrib, Herbert Jaeger

3. Ideal regularization for learning kernels from labels
Pages: 22-34
Author(s): Binbin Pan, Jianhuang Lai, Lixin Shen

4. Grid topologies for the self-organizing map
Pages: 35-48
Author(s): Ezequiel López-Rubio, Antonio Díaz Ramos

5. Synaptic dynamics: Linear model and adaptation algorithm
Pages: 49-68
Author(s): Ali Yousefi, Alireza A. Dibazar, Theodore W. Berger

Thursday 29 May 2014

International Neural Network Society Call for Nominations for Senior Member

The International Neural Network Society (INNS) is calling for nominations for Senior Member. The requirements for Senior Member are as follows:

1. A regular or affiliate member of the INNS, who has been an INNS member for at least 5 consecutive years, can be nominated by an INNS member for Senior Member.

2. The nominee must have demonstrated a significant contribution to the theory and/or applications and/or education and promotion of the subject discipline, and this must be stated in the nomination letter.

3. Final confirmation of the 2014 Senior Members will be made by the INNS Board of Governors and appropriate announcements will then be made, at least on the INNS website, www.inns.org, and in the INNS magazine.

4. New Senior Members will receive an updated membership certificate.

For 2014, nomination letters and a CV of the candidate can be sent via e-mail to the INNS VP for Membership, Irwin King at king@cse.cuhk.edu.hk with the subject line: 2014 INNS SM Nomination, by Friday, June 27, 2014.

Monday 26 May 2014

Neural Networks, Volume 55, Pages 1-110, July 2014

Neuroscience
1. Detecting cells using non-negative matrix factorization on calcium imaging data
Pages: 11-19
Author(s): Ryuichi Maruyama, Kazuma Maeda, Hajime Moroda, Ichiro Kato, Masashi Inoue, Hiroyoshi Miyakawa, Toru Aonishi

        
Learning Systems
2. Discrete-time online learning control for a class of unknown nonaffine nonlinear systems using reinforcement learning   
Pages: 30-41
Author(s): Xiong Yang, Derong Liu, Ding Wang, Qinglai Wei
        
3. Stochastic nonlinear time series forecasting using time-delay reservoir computers: Performance and universality   
Pages: 59-71
Author(s): Lyudmila Grigoryeva, Julie Henriques, Laurent Larger, Juan-Pablo Ortega
        
4. A general soft label based Linear Discriminant Analysis for semi-supervised dimensionality reduction   
Pages: 83-97
Author(s): Mingbo Zhao, Zhao Zhang, Tommy W.S. Chow, Bing Li

        
Mathematical and Computational Analysis
5. Exponential synchronization of delayed memristor-based chaotic neural networks via periodically intermittent control   
Pages: 1-10
Author(s): Guodong Zhang, Yi Shen

6. A collective neurodynamic optimization approach to bound-constrained nonconvex optimization
Pages: 20-29
Author(s): Zheng Yan, Jun Wang, Guocheng Li
        
7. Stability analysis of fractional-order Hopfield neural networks with time delays
Pages: 98-109
Author(s): Hu Wang, Yongguang Yu, Guoguang Wen

        
Engineering and Applications
8. Towards limb position invariant myoelectric pattern recognition using time-dependent spectral features   
Pages: 42-58
Author(s): Rami N. Khushaba, Maen Takruri, Jaime Valls Miro, Sarath Kodagoda
        
9. Model, analysis, and evaluation of the effects of analog VLSI arithmetic on linear subspace-based image recognition   
Pages: 72-82
Author(s): Gonzalo Carvajal, Miguel Figueroa

Monday 19 May 2014

Call for papers: IJCNN 2015

The 2015 International Joint Conference on Neural Networks will be held at the Killarney Convention Centre in Killarney, Ireland, July 12–16, 2015. The conference is organized jointly by the International Neural Network Society and the IEEE Computational Intelligence Society, and is the premiere international meeting for researchers and other professionals in neural networks and related areas.

The range of topics covered include, but is not limited to the following. (See http://ijcnn.org/2015 for a more detailed list of topics).
  • Neural network theory & models
  • Pattern recognition
  • Computational neuroscience 
  • Machine learning
  • Cognitive models 
  • Collective intelligence
  • Brain-machine interfaces 
  • Hybrid systems
  • Embodied robotics 
  • Self-aware systems
  • Evolutionary neural systems 
  • Data mining
  • Neurodynamics 
  • Sensor networks
  • Neuroinformatics 
  • Agent-based systems
  • Neuroengineering 
  • Computational biology
  • Hardware, memristors 
  • Bioinformatics
  • Neural network applications 
  • Artificial life
  • Machine vision 
  • Connectomics
  • Big data 
  • Deep learning
The conference will feature:
  • Contributed technical talks and posters of latest research from around the world.
  • Plenary lecturers by world-famous researchers in neural networks and related fields.
  • Special sessions covering topics of active current interest.
  • Pre-conference tutorials and post-conference workshops with presentations by experts.
  • Challenging competitions on applying neural networks to hard computational problems.

Important Dates

Special session & competition proposals submission: November 10, 2014
Tutorial and workshop proposal submission: December 15, 2014
Paper submission: January 15, 2015
Paper decision notification: March 15, 2015
Camera-ready submission: April 15, 2015

Organizing Committee

General Chair
De-Shuang Huang, Tongji University, China
dshuang@tongji.edu.cn 

Program Chair
Yoonsuck Choe, Texas A&M University, USA
choe@tamu.edu
 
Technical Program Co-Chair
Haibo He, University of Rhode Island, USA
he@ele.uri.edu
 
Technical Program Co-Chair
Asim Roy, Arizona State University, USA
Asim.Roy@asu.edu
 
Plenary Chair
Carlo Morabito, Mediterranea Univ., Italy
 
Special Sessions Chair
Mike Gashler, University of Arkansas, USA
 
Tutorials Chair
Martin McGinnity, University of Ulster, UK
 
Workshop Chair
Pierre-Yves Oudeyer, Ensta Paris Tech, France
 
Poster Session Chair
Xiao-Hua (Helen) Yu, Cal Polytech Univ., USA
 
Competition Chair
Abir Hussain, Liverpool John Moores U., UK
 
Panels Chair
Juyang (John) Weng, Michigan State U., USA
 
Awards Chair
Plamen Angelov, Lancaster University, UK
 
Web Reviews Chair
Tomasz Cholewo, Lexmark Int’l Inc., US
 
Sponsors & Exhibits Chair
Hanning Zhou, Zhigu Technology, China
 
Publications Chair
Amir Hussain, University of Stirling, UK
 
International Liaison
Nikola Kasabov, Auckland U. of Tech., New Zealand
 
European Liaison
Peter Erdi, Kalamazoo College, USA
 

Publicity Co-Chair
Yun Raymond Fu, Northeastern Univ., USA
 
Publicity Co-Chair
Bill Howell, Natural Resources Canada, Canada
 
Local Arrangements Chair
Kang Li, Queens Univ., Belfast, UK
 
Webmaster
Jaerock Kwon, Kettering University, USA

Wednesday 23 April 2014

Neural Networks Volume 54, Pages 1-122, June 2014

Neural Networks Letters

1. Interaction of feedforward and feedback streams in visual cortex in a firing-rate model of columnar computations  
Author(s): Tobias Brosch, Heiko Neumann
Pages: 11-16
 

Learning Systems

2. Learning invariant object recognition from temporal correlation in a hierarchical network  
Author(s): Markus Lessmann, Rolf P. Würtz
Pages: 70-84
   
3. Growing Neural Gas approach for obtaining homogeneous maps by restricting the insertion of new nodes 
Author(s): Yuri Quintana-Pacheco, Daniel Ruiz-Fernández, Agustín Magrans-Rico
Pages: 95-102
   

Mathematical and Computational Analysis

4. An improved robust stability result for uncertain neural networks with multiple time delays 
Author(s): Sabri Arik
Pages: 1-10
   
5. Solving the linear interval tolerance problem for weight initialization of neural networks 
Author(s): S.P. Adam, D.A. Karras, G.D. Magoulas, M.N. Vrahatis
Pages: 17-37
   
6. Necessary and sufficient condition for multistability of neural networks evolving on a closed hypercube 
Author(s): Mauro Di Marco, Mauro Forti, Massimo Grazzini, Luca Pancioni
Pages: 38-48

7. Stable locality sensitive discriminant analysis for image recognition 
Author(s): Quanxue Gao, Jingjing Liu, Kai Cui, Hailin Zhang, Xiaogang Wang
Pages: 49-56

8. Global asymptotic stability analysis for delayed neural networks using a matrix-based quadratic convex approach 
Author(s): Xian-Ming Zhang, Qing-Long Han
Pages: 57-69

9. Impulsive synchronization schemes of stochastic complex networks with switching topology: Average time approach 
Author(s): Chaojie Li, Wenwu Yu, Tingwen Huang
Pages: 85-94

10. New criterion of asymptotic stability for delay systems with time-varying structures and delays 
Author(s): Bo Liu, Wenlian Lu, Tianping Chen
Pages: 103-111

11. A systematic method for analyzing robust stability of interval neural networks with time-delays based on stability criteria 
Author(s): Zhenyuan Guo, Jun Wang, Zheng Yan
Pages: 112-122

Tuesday 1 April 2014

Neural Networks Volume 53, pages 1-172, May 2014

Neural Networks Letters

1. Further results on robustness analysis of global exponential stability of recurrent neural networks with time delays and random disturbances
Author(s): Weiwei Luo, Kai Zhong, Song Zhu, Yi Shen
Pages: 127-133
   
2. Fastest strategy to achieve given number of neuronal firing in theta model  
Author(s): Jiaoyan Wang, Qingyun Wang, Guanrong Chen
Pages: 134-145
   
3. Matrix measure strategies for stability and synchronization of inertial BAM neural network with time delays  
Author(s): Jinde Cao, Ying Wan
Pages: 165-172
   

Learning Systems

4. Cross-person activity recognition using reduced kernel extreme learning machine
Author(s): Wan-Yu Deng, Qing-Hua Zheng, Zhong-Min Wang
Pages: 1-7
   
5. Robust head pose estimation via supervised manifold learning
Author(s): Chao Wang, Xubo Song
Pages: 15-25
   
6. Assist-as-needed robotic trainer based on reinforcement learning and its application to dart-throwing
Author(s): Chihiro Obayashi, Tomoya Tamei, Tomohiro Shibata
Pages: 52-60
   
7. Kernel learning at the first level of inference
Author(s): Gavin C. Cawley, Nicola L.C. Talbot
Pages: 69-80
   
8. Similarity preserving low-rank representation for enhanced data representation and effective subspace learning
Author(s): Zhao Zhang, Shuicheng Yan, Mingbo Zhao
Pages: 81-94
   
9. Learning using privileged information: SVM+ and weighted SVM
Author(s): Maksim Lapin, Matthias Hein, Bernt Schiele
Pages: 95-108
   
10. Safe semi-supervised learning based on weighted likelihood
Author(s): Masanori Kawakita, Jun’ichi Takeuchi
Pages: 146-164
   

Mathematical and Computational Analysis

11. Synchronization control of memristor-based recurrent neural networks with perturbations
Author(s): Weiping Wang, Lixiang Li, Haipeng Peng, Jinghua Xiao, Yixian Yang
Pages: 8-14
   
12. Effects of asymmetric coupling and self-coupling on metastable dynamical transient rotating waves in a ring of sigmoidal neurons
Author(s): Yo Horikawa
Pages: 26-39
   
13. Generalization performance of Gaussian kernels SVMC based on Markov sampling
Author(s): Jie Xu, Yuan Yan Tang, Bin Zou, Zongben Xu, Luoqing Li, Yang Lu
Pages: 40-51

14. Convergence behavior of delayed discrete cellular neural network without periodic coefficients
Author(s): Jinling Wang, Haijun Jiang, Cheng Hu, Tianlong Ma
Pages: 61-68

15. Multiple image mu-stability of neural networks with unbounded time-varying delays
Author(s): Lili Wang, Tianping Chen
Pages: 109-118

16. Extreme learning machine for ranking: Generalization analysis and applications
Author(s): Hong Chen, Jiangtao Peng, Yicong Zhou, Luoqing Li, Zhibin Pan
Pages: 119-126

Wednesday 5 February 2014

Neural Networks new articles 2 January - 3 February, 2014

1. Safe semi-supervised learning based on weighted likelihood  
Author(s): Masanori Kawakita, Jun’ichi Takeuchi
   
2. Effects of asymmetric and self coupling on metastable dynamical transient rotating waves in a ring of sigmoidal neurons  
Author(s): Yo Horikawa

3. Kernel learning at the first level of inference  
Author(s): Gavin C. Cawley, Nicola L.C. Talbot
   
4. Convergence behavior of delayed discrete cellular neural network without periodic coefficients
Author(s): Jinling Wang, Haijun Jiang, Cheng Hu, Tianlong Ma
    
5. Generalization performance of Gaussian kernels SVMC based on Markov sampling 
Author(s): Jie Xu, Yuan Yan Tang, Bin Zou, Zongben Xu, Luoqing Li, Yang Lu

6. Assist-as-needed robotic trainer based on reinforcement learning and its application to dart-throwing  
Author(s): Chihiro Obayashi, Tomoya Tamei, Tomohiro Shibata
   
7. Cross-person activity recognition using reduced kernel extreme learning machine 
Author(s): Wan-Yu Deng, Qing-Hua Zheng, Zhong-Min Wang
   
8. Robust head pose estimation via supervised manifold learning  
Author(s): Chao Wang, Xubo Song

9. Synchronization control of memristor-based recurrent neural networks with perturbations  
Author(s): Weiping Wang, Lixiang Li, Haipeng Peng, Jinghua Xiao, Yixian Yang

Monday 27 January 2014

Neural Networks, Volume 51, March 2014

1. Editorial Board  
Pages IFC

Neuroscience

2. Global Mittag-Leffler stability and synchronization of memristor-based fractional-order neural networks  
Pages: 1-8
Author(s): Jiejie Chen, Zhigang Zeng, Ping Jiang
   

Learning Systems

3. Feature selection and multi-kernel learning for sparse representation on a manifold  
Pages: 9-16
Author(s):Jim Jing-Yan Wang, Halima Bensmail, Xin Gao
   
4. Long-term time series prediction using OP-ELM
Pages: 50-56
Author(s):Alexander Grigorievskiy, Yoan Miche, Anne-Mari Ventelä, Eric Séverin, Amaury Lendasse
   
5. Least Square Fast Learning Network for modeling the combustion efficiency of a 300WM coal-fired boiler
Pages: 57-66
Author(s):Guoqiang Li, Peifeng Niu, Huaibao Wang, Yongchao Liu
   

Mathematical and Computational Analysis

6. Neural network for solving convex quadratic bilevel programming problems 
Pages: 17-25
Author(s):Xing He, Chuandong Li, Tingwen Huang, Chaojie Li
   
7. Stability analysis of switched stochastic neural networks with time-varying delays  
Pages: 39-49
Author(s):Xiaotai Wu, Yang Tang, Wenbing Zhang
   
8. Lagrangian support vector regression via unconstrained convex minimization  
Pages: 67-79
Author(s):S. Balasundaram, Deepak Gupta, Kapil
   
9. Periodicity and global exponential stability of generalized Cohen–Grossberg neural networks with discontinuous activations and mixed delays
Pages: 80-95
Author(s):Dongshu Wang, Lihong Huang
   

Engineering and Applications

10. A generalized analog implementation of piecewise linear neuron models using CCII building blocks  
Pages: 26-38
Author(s):Hamid Soleimani, Arash Ahmadi, Mohammad Bavandpour, Ozra Sharifipoor
   
11. Current Events  
Pages I-II