Excerpts of research in brain sciences and neural networks in Singapore

We summarize some of the key research areas in brain sciences and neural networks that have recently been or are being worked on by researchers in Singapore. Researchers in Singapore are developing theory of neural networks, notably improved radial basis function networks, fuzzy neural networks, and fast learning neural networks. Applications of neural networks include bioinformatics, multimedia, data mining, and communications. Researchers are also working with neurophysiologists on functional brain imaging and brain disease analysis.

[1]  W L Nowinski,et al.  Planning and simulation of neurosurgery in a virtual reality environment. , 2000, Neurosurgery.

[2]  Ruowei Zhou,et al.  POPFNN-AAR(S): a pseudo outer-product based fuzzy neural network , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[3]  Jagath C Rajapakse,et al.  Multi-class support vector machines for protein secondary structure prediction. , 2003, Genome informatics. International Conference on Genome Informatics.

[4]  Vladimir Brusic,et al.  MAGE-6 encodes HLA-DRbeta1*0401-presented epitopes recognized by CD4+ T cells from patients with melanoma or renal cell carcinoma. , 2003, Clinical cancer research : an official journal of the American Association for Cancer Research.

[5]  Qi Tian,et al.  Gabor wavelet associative memory for face recognition , 2005, IEEE Trans. Neural Networks.

[6]  J C Rajapakse,et al.  Random‐grid stereologic volumetry of MR head scans , 2000, Journal of magnetic resonance imaging : JMRI.

[7]  Wei Lu,et al.  ICA with Reference , 2006, Neurocomputing.

[8]  Lipo Wang,et al.  Data dimensionality reduction with application to simplifying RBF network structure and improving classification performance , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[9]  Jagath C. Rajapakse,et al.  Bayesian approach to segmentation of statistical parametric maps , 2001, IEEE Transactions on Biomedical Engineering.

[10]  Seng Hong Seah,et al.  Dragon gene start finder: an advanced system for finding approximate locations of the start of gene transcriptional units. , 2003, Genome research.

[11]  Michel Pasquier,et al.  Fuzzylot: a novel self-organising fuzzy-neural rule-based pilot system for automated vehicles , 2001, Neural Networks.

[12]  Wei Lu,et al.  Eliminating indeterminacy in ICA , 2003, Neurocomputing.

[13]  Michel Pasquier,et al.  POPFNN-CRI(S): pseudo outer product based fuzzy neural network using the compositional rule of inference and singleton fuzzifier , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[14]  Wieslaw L. Nowinski,et al.  Computerized Brain Atlases for Surgery of Movement Disorders , 2001 .

[15]  Aamer Aziz,et al.  A knowledge-driven algorithm for a rapid and automatic extraction of the human cerebral ventricular system from MR neuroimages , 2004, NeuroImage.

[16]  Hiok Chai Quek,et al.  Pseudo-outer product based fuzzy neural network fingerprint verification system , 2001, Neural Networks.

[17]  Markus Werner,et al.  A neural network approach to distributed adaptive routing of LEO intersatellite link traffic , 1998, VTC '98. 48th IEEE Vehicular Technology Conference. Pathway to Global Wireless Revolution (Cat. No.98CH36151).

[18]  Hiok Chai Quek,et al.  GenSo-EWS: a novel neural-fuzzy based early warning system for predicting bank failures , 2004, Neural Networks.

[19]  Ruowei Zhou,et al.  Antiforgery: a novel pseudo-outer product based fuzzy neural network driven signature verification system , 2002, Pattern Recognit. Lett..

[20]  Hiok Chai Quek,et al.  Falcon: neural fuzzy control and decision systems using FKP and PFKP clustering algorithms , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[21]  Loi Sy Ho,et al.  Splice site detection with a higher-order markov model implemented on a neural network. , 2003, Genome informatics. International Conference on Genome Informatics.

[22]  Wieslaw Lucjan Nowinski,et al.  Talairach-Tournoux brain atlas registration using a metalforming principle-based finite element method , 2001, Medical Image Anal..

[23]  Lipo Wang,et al.  Image restoration using chaotic simulated annealing , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

[24]  Guang-Bin Huang,et al.  Extreme learning machine: a new learning scheme of feedforward neural networks , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

[25]  Meng Joo Er,et al.  Online adaptive fuzzy neural identification and control of a class of MIMO nonlinear systems , 2003, IEEE Trans. Fuzzy Syst..

[26]  Meng Joo Er,et al.  Robust adaptive control of robot manipulators using generalized fuzzy neural networks , 2003, IEEE Trans. Ind. Electron..

[27]  Yakov Frayman,et al.  A dynamically-constructed fuzzy neural controller for direct model reference adaptive control of multi-input-multi-output nonlinear processes , 2002, Soft Comput..

[28]  Wieslaw L. Nowinski,et al.  A rapid algorithm for robust and automatic extraction of the midsagittal plane of the human cerebrum from neuroimages based on local symmetry and outlier removal , 2003, NeuroImage.

[29]  Ravinda G. N. Meegama,et al.  NURBS-Based Segmentation of the Brain in Medical Images , 2003, Int. J. Pattern Recognit. Artif. Intell..