Solving Numerical Computation Problems Using a Few Artificial Neurons


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Abstract


Numerical Computation is widely used in engineering problems. In this paper, it is shown that many Numerical Computation problems can be expressed by one or few artificial neurons. Then, the task of solving each of the problems is converted to the task of training the neurons in order to find the weights of the neurons. The weights of the neurons contain the solution to the problem at hand. As a result, to solve a Numerical Computation problem, there is no need to develop special algorithms for the problem. Experimental results demonstrate that this novel approach is successful in solving several different Numerical Computation problems and may pave the way to tackle other Numerical Computation problems by using only neural networks without developing specific algorithms
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Keywords


Neural Networks; Numerical Computation; Gradient Descent; Levenberg-Marquardt

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