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In this work, we develop a simple yet practical algorithm for constructing derivative free iterative methods of higher convergence orders. The algorithm can be easily implemented in software packages for achieving desired convergence orders. Convergence analysis shows that the algorithm can develop methods of various convergence orders which is also supported through the numerical work. Computational...
In this paper, a novel operator method is proposed for solving fuzzy linear differential equations under the assumption of strongly generalized differentiability. To this end, the equivalent integral form of the original problem is obtained then by using its lower and upper functions the solutions in the parametric forms are determined. The proposed method is illustrated with numerical examples.
Despite all advances in parsing, parser size, conflict resolution and error recovery are still of important consideration. In this research, we propose a predictive bottom-up parser. The parser is implemented in two versions. Both versions constitute an algorithm that simulates the run of a shift–reduce automaton, defined and constructed in a way that integrates its parsing actions with reduction...
Zhang neural networks (ZNN), a special kind of recurrent neural networks (RNN) with implicit dynamics, have recently been introduced to generalize to the solution of online time-varying problems. In comparison with conventional gradient-based neural networks, such RNN models are elegantly designed by defining matrix-valued indefinite error functions. In this paper, we generalize, investigate and analyze...
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