Fuzzy Artmap+Research Papers

Fuzzy Artmap+Research Papers-15
For training the MLP two different variants of the backpropagation algorithm are used: the BPLRF algorithm (backpropagation with plummeting learning rate factor) for the benchmarks, and the BST algorithm (backpropagation with selective training) for the Farsi OCR problem.The results obtained on all of the three case studies with the MLP and the SFAM, embedded in their customized systems, show that the SFAM's convergence in fast-training mode, is faster than that of MLP, and online operation of the MLP is faster than that of the SFAM.It could be something as simple as a run away script or learning how to better use E-utilities, for more efficient work such that your work does not impact the ability of other researchers to also use our site.

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On the benchmark problems the MLP has much better recognition rate than the SFAM.

On the Farsi OCR problem, the recognition error of the SFAM is higher than that of the MLP on ill-engineered datasets, but equal on well-engineered ones. its capability to increase the size of the network in order to learn new patterns, as well as its simple parameter adjustment, remain unchallenged by the MLP.

The results focus primarily on stability and robustness, which are studied in light of the presence of externally generated exogenous input signals. Obtained results answers the question of asymptotic stabilization and tracking of a desired trajectory in the presence of a dynamic exosystem.

The results confirmed the working theory of robust stabilization using output feedback techniques, borne out of differential-geometric observer design principles.

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International Journal of Fuzzy Logic Systems (IJFLS) is an open access peer-reviewed journal that covers all topics in theoretical, experimental and applied fuzzy techniques and systems. more International Journal of Fuzzy Logic Systems (IJFLS) is an open access peer-reviewed journal that covers all topics in theoretical, experimental and applied fuzzy techniques and systems.

It is aimed to bring together researchers and developers from both academia and industry to discuss the latest scientific and theoretical advances in this field, and to demonstrate the state-of-the-art systems.

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