ライブラリ登録: Guest
Journal of Automation and Information Sciences

年間 12 号発行

ISSN 印刷: 1064-2315

ISSN オンライン: 2163-9337

SJR: 0.173 SNIP: 0.588 CiteScore™:: 2

Indexed in

Self-Learning Cascade Spiking Neural Network for Fuzzy Clustering Based on Group Method of Data Handling

巻 45, 発行 3, 2013, pp. 23-33
DOI: 10.1615/JAutomatInfScien.v45.i3.30
Get accessGet access

要約

The fuzzy clustering problem in the presence of overlapping classes is considered. To solve the problem, it is introduced the architecture and learning algorithm of a fuzzy spiking neural network, generalizing neural networks of the third generation, which at present are developing intensively and have a number of advantages over traditional computational intelligence systems. The spiking neuron is described as a nonlinear dynamic system, which simplifies the hardware implementation. For problems with high dimension of input vectors-images it is proposed to use the hybrid architecture, which is based on a combination of cascade and GMDH-neural networks with self-learning cascade spiking neural networks, used as nodes, and ensures the increased speed of information processing.

によって引用された
  1. Kovalchuk Anatoliy, Lotoshynska Natalia, Assessment of damage to buildings in areasemergency situations, 2016 IEEE First International Conference on Data Stream Mining & Processing (DSMP), 2016. Crossref

  2. Peleshko Dmytro, Rak Taras, Peleshko Marta, Izonin Ivan, Batyuk Danylo, Two-frames image superresolution based on the aggregate divergence matrix, 2016 IEEE First International Conference on Data Stream Mining & Processing (DSMP), 2016. Crossref

  3. Tkachenko Roman, Tkachenko Pavlo, Izonin Ivan, Tsymbal Yurij, Learning-Based Image Scaling Using Neural-Like Structure of Geometric Transformation Paradigm, in Advances in Soft Computing and Machine Learning in Image Processing, 730, 2018. Crossref

  4. Tkachenko Roman, Doroshenko Anastasiya, Izonin Ivan, Tsymbal Yurii, Havrysh Bohdana, Imbalance Data Classification via Neural-Like Structures of Geometric Transformations Model: Local and Global Approaches, in Advances in Computer Science for Engineering and Education, 754, 2019. Crossref

  5. Vynokurova Olena, Peleshko Dmytro, Oskerko Semen, Lutsan Vitalii, Peleshko Marta, Multidimensional Wavelet Neuron for Pattern Recognition Tasks in the Internet of Things Applications, in Advances in Computer Science for Engineering and Education, 754, 2019. Crossref

  6. Stepashko Volodymyr, On the Self-organizing Induction-Based Intelligent Modeling, in Advances in Intelligent Systems and Computing III, 871, 2019. Crossref

  7. Babichev S., Lytvynenko V., Korobchynskyi M., Sokur I., Computational Epigenetics in Lung Cancer, in Computational Epigenetics and Diseases, 2019. Crossref

  8. Zgurovsky Michael Z., Zaychenko Yuriy P., Deep Neural Networks and Hybrid GMDH-Neuro-fuzzy Networks in Big Data Analysis, in Big Data: Conceptual Analysis and Applications, 58, 2020. Crossref

  9. Korenevskii Nikolai, Artemenko Michail, Dobrovollsky Ilya, Synthesis of an Antecedent of the Productional Rule by Logical Neural Networks on a Basis of Architecture Similar of Group Method of Data Handling, 2018 International Russian Automation Conference (RusAutoCon), 2018. Crossref

  10. Bodyanskiy Yevgeniy, Boiko Olena, Zaychenko Yuriy, Hamidov Galib, Zelikman Anna, The Hybrid GMDH-Neo-fuzzy Neural Network in Forecasting Problems in Financial Sphere, 2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC), 2020. Crossref

  11. Bodyanskiy Yevgeniy, Boiko Olena, Zaychenko Yuriy, Hamidov Galib, Evolving GMDH-neuro-fuzzy system with small number of tuning parameters, 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), 2017. Crossref

  12. Bodyanskiy Yevgeniy, Boiko Olena, Zaychenko Yuriy, Hamidov Galib, Evolving Hybrid GMDH-Neuro-Fuzzy Network and its Applications, 2018 IEEE First International Conference on System Analysis & Intelligent Computing (SAIC), 2018. Crossref

  13. Bodyanskiy Yevgeniy, Zaychenko Yuriy, Boiko Olena, Hamidov Galib, Zelikman Anna, Structure Optimization and Investigations of the Hybrid GMDH-Neo-fuzzy Neural Networks in Forecasting Problems, in System Analysis & Intelligent Computing, 1022, 2022. Crossref

  14. Vynokurova Olena, Peleshko Dmytro, Borzov Yuriy, Oskerko Semen, Voloshyn Viktor, Hybrid Multidimensional Wavelet-Neuro-System and its Learning Using Cross Entropy Cost Function in Pattern Recognition, 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP), 2018. Crossref

  15. Liu Fang, Yang Jie, Pedrycz Witold, Wu Wei, A New Fuzzy Spiking Neural Network Based on Neuronal Contribution Degree, IEEE Transactions on Fuzzy Systems, 30, 7, 2022. Crossref

Begell Digital Portal Begellデジタルライブラリー 電子書籍 ジャーナル 参考文献と会報 リサーチ集 価格及び購読のポリシー Begell House 連絡先 Language English 中文 Русский Português German French Spain