Saravanan Shanmugam, Syed Ali Muhammed & Gyu M. Lee. (2019) Finite-time extended dissipativity of delayed Takagi–Sugeno fuzzy neural networks using a free-matrix-based double integral inequality. Neural Computing and Applications 32:12, pages 8517-8528.
Crossref

Yunlong Lu, Wenyu Li & Hongwei Wang. (2020) A Batch Variable Learning Rate Gradient Descent Algorithm With the Smoothing L 1/2 Regularization for Takagi-Sugeno Models . IEEE Access 8, pages 100185-100193.
Crossref

Tariq Kamal, Murat Karabacak, Frede Blaabjerg, Syed Zulqadar Hassan & Luis M. Fernández-Ramírez. (2019) A novel Lyapunov stable higher order B-spline online adaptive control paradigm of photovoltaic systems. Solar Energy 194, pages 530-540.
Crossref

Jerome Mendes, Antonio Craveiro & Rui Araujo. (2018) Iterative Design of a Mamdani Fuzzy Controller. Iterative Design of a Mamdani Fuzzy Controller.

H.R. Khosravani, A.E. Ruano & P.M. Ferreira. (2016) A convex hull-based data selection method for data driven models. Applied Soft Computing 47, pages 515-533.
Crossref

M. G. Ruano & A. E. Ruano. (2016) Towards ultrasound hyperthermia safe treatments using computational intelligence techniques. Towards ultrasound hyperthermia safe treatments using computational intelligence techniques.

Alexandra-Iulia Stinean, Claudia-Adina Bojan-Dragos, Radu-Emil Precup, Stefan Preitl & Emil M. Petriu. (2015) Takagi-Sugeno PD+I fuzzy control of processes with variable moment of inertia. Takagi-Sugeno PD+I fuzzy control of processes with variable moment of inertia.

Min Gan, Han-Xiong Li & Hui Peng. (2015) A Variable Projection Approach for Efficient Estimation of RBF-ARX Model. IEEE Transactions on Cybernetics 45:3, pages 462-471.
Crossref

Chang Liu, Honglun Wang & Peng Yao. (2014) On terrain-aided navigation for unmanned aerial vehicle using B-spline neural network and extended Kalman filter. On terrain-aided navigation for unmanned aerial vehicle using B-spline neural network and extended Kalman filter.

János Botzheim & Péter Földesi. (2014) Novel calculation of fuzzy exponent in the sigmoid functions for fuzzy neural networks. Neurocomputing 129, pages 458-466.
Crossref

Sheng Chen, Xia Hong, Yu Gong & Chris J. Harris. (2013) Digital Predistorter Design Using B-Spline Neural Network and Inverse of De Boor Algorithm. IEEE Transactions on Circuits and Systems I: Regular Papers 60:6, pages 1584-1594.
Crossref

Cristiano L. Cabrita, António E. Ruano, Pedro M. Ferreira & László T. Kóczy. 2013. Soft Computing Applications. Soft Computing Applications 543 559 .

Cristiano L. Cabrita, Antonio E. Ruano, Pedro M. Ferreira & Laszlo T. Koczy. (2012) Extending the functional training approach for B-splines. Extending the functional training approach for B-splines.

António E Ruano, Cristiano L. Cabrita, Pedro M. Ferreira & László T. Kóczy. (2012) Exploiting the functional training approach in B-Splines. IFAC Proceedings Volumes 45:4, pages 127-132.
Crossref

Antonio E Ruano, Cristiano L. Cabrita & Pedro M. Ferreira. (2011) Towards a more analytical training of neural networks and neuro-fuzzy systems. Towards a more analytical training of neural networks and neuro-fuzzy systems.

Zsolt Danyadi, Krisztian Balazs & Laszlo T. Koczy. (2010) Using multiple populations of memetic algorithms for fuzzy rule-base optimization. Using multiple populations of memetic algorithms for fuzzy rule-base optimization.

Cristiano L. Cabrita, Antonio E. B. Ruano & Laszlo T. Koczy. (2010) A new domain decomposition for B-spline Neural Networks. A new domain decomposition for B-spline Neural Networks.

J. Botzheim, C. Cabrita, L. T. Kóczy & A. E. Ruano. (2009) Fuzzy rule extraction by bacterial memetic algorithms. International Journal of Intelligent Systems 24:3, pages 312-339.
Crossref

János Botzheim, Cristiano Cabrita, László T. Kóczy & Antonio E. Ruano. (2007) Genetic and Bacterial Programming for B-Spline Neural Networks Design. Journal of Advanced Computational Intelligence and Intelligent Informatics 11:2, pages 220-231.
Crossref

C. Cabrita, J. Botzheim, A.E.B. Ruano & L.T. Koczy. (2005) An hybrid training method for B-spline neural networks. An hybrid training method for B-spline neural networks.

J. Botzheim, C. Cabrita, L.T. Koczy & A.E. Ruano. (2004) Estimating fuzzy membership functions parameters by the Levenberg-Marquardt algorithm. Estimating fuzzy membership functions parameters by the Levenberg-Marquardt algorithm.

António E. B. Ruano. 2003. Artificial Neural Nets Problem Solving Methods. Artificial Neural Nets Problem Solving Methods 457 464 .

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Order Reprints Request Corporate Permissions

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

Request Academic Permissions

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.

People also read
Recommended articles
Cited by

To cite this article:

Reference style: APA Chicago Harvard

Citation copied to clipboard

Reference styles above use APA (6th edition), Chicago (16th edition) & Harvard (10th edition)

Download citation

Download a citation file in RIS format that can be imported by citation management software including EndNote, ProCite, RefWorks and Reference Manager.

Choose format: RIS BibTex RefWorks Direct Export

Choose options: Citation Citation & abstract Citation & references

Supervised training algorithms for B-Spline neural networks and neuro-fuzzy systems

Articles from other publishers (22)

Information for

Open access

Opportunities

Help and information

Your download is now in progress and you may close this window

Login or register to access this feature