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Nikola K. Kasabov: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Simei Gomes Wysoski, Lubica Benuskova, Nikola K. Kasabov
    Adaptive Learning Procedure for a Network of Spiking Neurons and Visual Pattern Recognition. [Citation Graph (0, 0)][DBLP]
    ACIVS, 2006, pp:1133-1142 [Conf]
  2. Nikola K. Kasabov
    Hybrid Connectionist Rule-Based Systems. [Citation Graph (0, 0)][DBLP]
    AIMSA, 1990, pp:227-235 [Conf]
  3. Nikola K. Kasabov, Daniel Nikovski
    Prognostic Expert Systems on a Hybrid Connectionist Environment. [Citation Graph (0, 0)][DBLP]
    AIMSA, 1992, pp:141-148 [Conf]
  4. Max Bailey, Nikola K. Kasabov, Peter Mason, Andrew R. Gray, Tico Cohen
    Hybrid Systems for Prediction - A Case Study of Predicting Effluent Flow to a Sewage Plant. [Citation Graph (0, 0)][DBLP]
    ANNES, 1995, pp:261-264 [Conf]
  5. Max Bailey, Clive Solomon, Nikola K. Kasabov, Simon Greig
    Hybrid Systems for Medical Data Analysis and Decision Making - A Case Study on Varicose Vein Disorders . [Citation Graph (0, 0)][DBLP]
    ANNES, 1995, pp:265-268 [Conf]
  6. Nikola K. Kasabov, S. Sinclair, Richard Kilgour, C. Watson, Mark R. Laws, Diana Kassabova
    Intelligent human computer interfaces and the case study of building English-to-Maori talking dictionary. [Citation Graph (0, 0)][DBLP]
    ANNES, 1995, pp:294-297 [Conf]
  7. Liang Goh, Qun Song, Nikola K. Kasabov
    A Novel Feature Selection Method to Improve Classification of Gene Expression Data. [Citation Graph (0, 0)][DBLP]
    APBC, 2004, pp:161-166 [Conf]
  8. Nikola K. Kasabov, M. Middlemiss, T. Lane
    A Generic Connectionist-Based Method for On-Line Feature Selection and Modelling with a Case Study of Gene Expression Data Analysis. [Citation Graph (0, 0)][DBLP]
    APBC, 2003, pp:199-202 [Conf]
  9. Nikola K. Kasabov, G. T. Bijev, B. J. Jechev
    Hierarchical discrete systems and realisation of parallel algorithms. [Citation Graph (0, 0)][DBLP]
    CONPAR, 1981, pp:414-422 [Conf]
  10. Nikola K. Kasabov, S. H. Petkov
    Neural Networks and Logic Programming - a Hybrid Model and its Applicability to Building Expert Systems. [Citation Graph (0, 0)][DBLP]
    ECAI, 1992, pp:287-288 [Conf]
  11. Brendon J. Woodford, Nikola K. Kasabov
    Ensembles of EFuNNs: An Architecture for a Mutlimodule Classifier. [Citation Graph (0, 0)][DBLP]
    FUZZ-IEEE, 2001, pp:1573-1576 [Conf]
  12. Da Deng, Nikola K. Kasabov
    An evolving localised learning model for on-line image colour quantisation. [Citation Graph (0, 0)][DBLP]
    ICIP (1), 2001, pp:906-909 [Conf]
  13. Nikola K. Kasabov
    ECOS: Evolving Connectionist Systems and the ECO Learning Paradigm. [Citation Graph (0, 0)][DBLP]
    ICONIP, 1998, pp:1232-1235 [Conf]
  14. Nikola K. Kasabov, Zeke S. H. Chan, Vishal Jain, Igor Sidorov, Dimiter S. Dimitrov
    Gene Regulatory Network Discovery from Time-Series Gene Expression Data - A Computational Intelligence Approach. [Citation Graph (0, 0)][DBLP]
    ICONIP, 2004, pp:1344-1353 [Conf]
  15. Qun Song, Nikola K. Kasabov
    TWRBF - Transductive RBF Neural Network with Weighted Data Normalization. [Citation Graph (0, 0)][DBLP]
    ICONIP, 2004, pp:633-640 [Conf]
  16. Michael J. Watts, Nikola K. Kasabov
    Genetic Algorithms for the Design of Fuzzy Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICONIP, 1998, pp:793-796 [Conf]
  17. Irena Koprinska, Nikola K. Kasabov
    Evolving Fuzzy Neural Network for Camera Operations Recognition. [Citation Graph (0, 0)][DBLP]
    ICPR, 2000, pp:2523-2526 [Conf]
  18. Nikola K. Kasabov
    Connectionist Fuzzy Production Systems. [Citation Graph (0, 0)][DBLP]
    Fuzzy Logic in Artificial Intelligence, 1993, pp:114-128 [Conf]
  19. Da Deng, Nikola K. Kasabov
    ESOM: An Algorithm to Evolve Self-Organizing Maps from On-Line Data Streams. [Citation Graph (0, 0)][DBLP]
    IJCNN (6), 2000, pp:3-8 [Conf]
  20. Nikola K. Kasabov
    Hybrid Connectionist Fuzzy Systems for Speech Recognition and the Use of Connectionist Production Systems. [Citation Graph (0, 0)][DBLP]
    IEEE/Nagoya-University World Wisepersons Workshop, 1994, pp:19-33 [Conf]
  21. Tianmin Ma, Qun Song, Nikola K. Kasabov, Mark Roger Marshall
    TWNFC - Transductive Neural-Fuzzy Classifier with Weighted Data Normalization and Its Application in Medicine. [Citation Graph (0, 0)][DBLP]
    CIMCA/IAWTIC, 2005, pp:479-484 [Conf]
  22. Qun Song, Nikola K. Kasabov, Tianmin Ma, Mark Roger Marshall
    Integrating regression formulas and kernel functions into locally adaptive knowledge-based neural networks: A case study on renal function evaluation. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence in Medicine, 2006, v:36, n:3, pp:235-244 [Journal]
  23. Nikola K. Kasabov
    Adaptation and interaction in dynamical systems: Modelling and rule discovery through evolving connectionist systems. [Citation Graph (0, 0)][DBLP]
    Appl. Soft Comput., 2006, v:6, n:3, pp:307-322 [Journal]
  24. Zeke S. H. Chan, Lesley Collins, Nikola K. Kasabov
    An efficient greedy K-means algorithm for global gene trajectory clustering. [Citation Graph (0, 0)][DBLP]
    Expert Syst. Appl., 2006, v:30, n:1, pp:137-141 [Journal]
  25. Zeke S. H. Chan, Nikola K. Kasabov, Lesley Collins
    A two-stage methodology for gene regulatory network extraction from time-course gene expression data. [Citation Graph (0, 0)][DBLP]
    Expert Syst. Appl., 2006, v:30, n:1, pp:59-63 [Journal]
  26. Zeke S. H. Chan, Nikola K. Kasabov
    Evolutionary Computation For On-Line And Off-Line Parameter Tuning Of Evolving Fuzzy Neural Networksc. [Citation Graph (0, 0)][DBLP]
    International Journal of Computational Intelligence and Applications, 2004, v:4, n:3, pp:309-0 [Journal]
  27. Nikola K. Kasabov, Hojjat Adeli, Nikhil R. Pal
    Introduction. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2005, v:15, n:1-2, pp:- [Journal]
  28. Lubica Benuskova, Vishal Jain, Simei Gomes Wysoski, Nikola K. Kasabov
    Computational Neurogenetic Modelling: a Pathway to New Discoveries in Genetic Neuroscience. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2006, v:16, n:3, pp:215-226 [Journal]
  29. Da Deng, Nikola K. Kasabov
    On-line pattern analysis by evolving self-organizing maps. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2003, v:51, n:, pp:87-103 [Journal]
  30. Nikola K. Kasabov
    On-line learning, reasoning, rule extraction and aggregation in locally optimized evolving fuzzy neural networks. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2001, v:41, n:1-4, pp:25-45 [Journal]
  31. Nikola K. Kasabov
    Adaptable neuro production systems. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 1996, v:13, n:2-4, pp:95-117 [Journal]
  32. Akbar Ghobakhlou, Michael J. Watts, Nikola K. Kasabov
    Adaptive speech recognition with evolving connectionist systems. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 2003, v:156, n:1-2, pp:71-83 [Journal]
  33. Nikola K. Kasabov
    Spoken language analysis, modeling and recognition - Cstatistical and adaptive connectionist approaches. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 2003, v:156, n:1-2, pp:1-2 [Journal]
  34. Nikola K. Kasabov, Kaoru Hirota
    Special Issue on Advanced Neuro-Fuzzy Techniques and Their Applications: Introduction. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 1997, v:101, n:3-4, pp:153-154 [Journal]
  35. Nikola K. Kasabov, Robert Kozma
    Methods and systems for intelligent human-computer interaction. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 2000, v:123, n:1-2, pp:1-2 [Journal]
  36. Nikola K. Kasabov, Robert Kozma, Michael J. Watts
    Phoneme-Based Speech Recognition via Fuzzy Neural Networks Modeling and Learning. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 1998, v:110, n:1-2, pp:61-79 [Journal]
  37. Nikola K. Kasabov, Jaesoo Kim, Michael J. Watts, Andrew R. Gray
    FuNN/2 - A Fuzzy Neural Network Architecture for Adaptive Learning and Knowledge Acquisition. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 1997, v:101, n:3-4, pp:155-175 [Journal]
  38. Nikola K. Kasabov, Eric O. Postma, H. Jaap van den Herik
    AVIS: a connectionist-based framework for integrated auditory and visual information processing. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 2000, v:123, n:1-2, pp:127-148 [Journal]
  39. Mark R. Laws, Richard Kilgour, Nikola K. Kasabov
    Modeling the emergence of bilingual acoustic clusters: a preliminary case study. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 2003, v:156, n:1-2, pp:85-107 [Journal]
  40. Nikola K. Kasabov
    The ECOS Framework and the ECO Learning Method for Evolving Connectionist Systems. [Citation Graph (0, 0)][DBLP]
    JACIII, 1998, v:2, n:6, pp:195-202 [Journal]
  41. Nikola K. Kasabov, Steven A. Israel, Brendon J. Woodford
    The Application of Hybrid Evolving Connectionist Systems to Image Classification. [Citation Graph (0, 0)][DBLP]
    JACIII, 2000, v:4, n:1, pp:57-65 [Journal]
  42. Nikola K. Kasabov, Robert Kozma
    Self-Organization and Adaptation in Intelligent Systems. [Citation Graph (0, 0)][DBLP]
    JACIII, 1998, v:2, n:6, pp:177- [Journal]
  43. Nikola K. Kasabov, Jaesoo Kim, Robert Kozma, Tico Cohen
    Rule Extraction from Fuzzy Neural Networks FuNN: A Method and a Real-World Application. [Citation Graph (0, 0)][DBLP]
    JACIII, 2001, v:5, n:4, pp:193-200 [Journal]
  44. Nikola K. Kasabov
    Fril - Fuzzy and Evidential Reasoning in Artificial Intelligence, by J. F. Baldwin, T. P. Martin, and B. W. Pilsworth. [Citation Graph (0, 0)][DBLP]
    JASIS, 1996, v:47, n:10, pp:790-791 [Journal]
  45. Zeke S. H. Chan, Nikola K. Kasabov, Lesley Collins
    A Hybrid Genetic Algorithm and Expectation Maximization Method for Global Gene Trajectory Clustering. [Citation Graph (0, 0)][DBLP]
    J. Bioinformatics and Computational Biology, 2005, v:3, n:5, pp:1227-1242 [Journal]
  46. Liang Goh, Nikola K. Kasabov
    An Integrated Feature Selection and Classification Method to Select Minimum Number of Variables on the Case Study of Gene Expression Data. [Citation Graph (0, 0)][DBLP]
    J. Bioinformatics and Computational Biology, 2005, v:3, n:5, pp:1107-1136 [Journal]
  47. Nikola K. Kasabov, Simon H. Lavington, S. Lin, C. Wang
    Model for exploiting associative matching in AI production systems. [Citation Graph (0, 0)][DBLP]
    Knowl.-Based Syst., 1995, v:8, n:1, pp:14-20 [Journal]
  48. Jaesoo Kim, Nikola K. Kasabov
    HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1999, v:12, n:9, pp:1301-1319 [Journal]
  49. Zeke S. H. Chan, Nikola K. Kasabov
    A Preliminary Study on Negative Correlation Learning via Correlation-Corrected Data (NCCD). [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 2005, v:21, n:3, pp:207-214 [Journal]
  50. Qun Song, Nikola K. Kasabov
    NFI: a neuro-fuzzy inference method for transductive reasoning. [Citation Graph (0, 0)][DBLP]
    IEEE T. Fuzzy Systems, 2005, v:13, n:6, pp:799-808 [Journal]
  51. Nikola K. Kasabov
    Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part B, 2001, v:31, n:6, pp:902-918 [Journal]
  52. Nikola K. Kasabov, Shaoning Pang
    Editorial. [Citation Graph (0, 0)][DBLP]
    Int. J. Comput. Syst. Signal, 2004, v:5, n:2, pp:1- [Journal]
  53. Akbar Ghobakhlou, Nikola K. Kasabov
    A Methodology and a System for Adaptive, Integrated Speech and Image Learning and Recognition. [Citation Graph (0, 0)][DBLP]
    Int. J. Comput. Syst. Signal, 2004, v:5, n:2, pp:2-16 [Journal]

  54. Spanning SVM Tree for Personalized Transductive Learning. [Citation Graph (, )][DBLP]


  55. Discovering Diagnostic Gene Targets and Early Diagnosis of Acute GVHD Using Methods of Computational Intelligence over Gene Expression Data. [Citation Graph (, )][DBLP]


  56. Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework. [Citation Graph (, )][DBLP]


  57. Evolving Brain-Gene Ontology System (EBGOS): Towards Integrating Bioinformatics and Neuroinformatics Data to Facilitate Discoveries. [Citation Graph (, )][DBLP]


  58. Computational Neurogenetic Modeling: A Methodology to Study Gene Interactions Underlying Neural Oscillations. [Citation Graph (, )][DBLP]


  59. r-SVMT: Discovering the knowledge of association rule over SVM classification trees. [Citation Graph (, )][DBLP]


  60. Evolving spiking neural networks for taste recognition. [Citation Graph (, )][DBLP]


  61. An adaptive model of person identification combining speech and image information. [Citation Graph (, )][DBLP]


  62. Soft computing methods to predict gene regulatory networks: An integrative approach on time-series gene expression data. [Citation Graph (, )][DBLP]


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