Oct 16, 2012 · Abstract: By following the inspirational work of McCulloch and Pitts [1], lots of neural networks have been proposed, developed and studied ...
By following the inspirational work of McCulloch and Pitts [1], lots of neural networks have been proposed, developed and studied for scientific research ...
NRNN is a special class of RNN, which originates from the research of HNN; it is proposed as a systematic approach to solving time- varying problems; and, it ...
RNN has a strong power to handle a sequence with temporal correlation and it has been widely utilized in solving time-varying problems [42,43], ...
By following the inspirational work of McCulloch and Pitts [1], lots of neural networks have been proposed, developed and studied for scientific research ...
Missing: Frontier]. | Show results with:Frontier].
In this paper, based on a one-neuron recurrent neural network, a novel k-winners-take-all (k -WTA) network is proposed and finite time convergence of the ...
In this letter, a novel recurrent neural network based on the gradient method is proposed for solving linear programming problems. Finite-time convergence ...
In this paper, a nonlinear activation function (NAF) is proposed to constructed three recurrent neural network (RNN) models.
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In this paper, a nonlinear activation function (NAF) is proposed to constructed three recurrent neural network (RNN) models.
Aug 6, 2024 · A discrete zeroing neural network (DZNN) method is proposed to solve the shortest path planning problem with a single starting point and a single target point.