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A new recurrent neural network (or say, net), i.e., Zhang Neural Network (ZNN), is recently proposed by Zhang et al for online time-varying matrix equations solving. Theoretical analysis, blocks modeling and verification results of Zhang neural network are investigated in this paper, in addition to the neural-solver design method and its comparable gradient neural network (GNN). Towards the final...
In view of the great potential in parallel processing and ready implementation via hardware, neural networks are now often employed to solve online matrix algebraic problems. Recently, a special kind of recurrent neural network has been proposed by Zhang et al, which could be generalized to solving online Lyapunov equation with time-varying coefficient matrices. In comparison with gradient-based neural...
For solving online the linear matrix equation AXB = C with time-varying coefficients, this paper presents a special kind of recurrent neural networks by using a design method recently proposed by Zhang et al. Compared with gradient neural networks (abbreviated as GNN, or termed as gradient-based neural networks), the resultant Zhang neural network (termed as such and abbreviated as ZNN hereafter for...
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