A single layer neural network for the solution of linear equations is presented. The proposed circuit is based on the standard Hopfield model albeit with the added flexibility that the interconnection weight matrix need not be symmetric. This results in an asymmetric Hopfield neural network capable of solving linear equations. PSPICE simulation results are given which verify the theoretical predictions. Experimental results for circuits set up to solve small problems further confirm the operation of the proposed circuit.

中文翻译：

---

单层非对称RNN：潜在的低硬件复杂度线性方程求解器

提出了用于求解线性方程组的单层神经网络。所提出的电路基于标准的Hopfield模型，尽管具有更大的灵活性，即互连权重矩阵不必对称。这导致了能够求解线性方程的非对称Hopfield神经网络。给出了PSPICE仿真结果，验证了理论预测。为解决小问题而设置的电路的实验结果进一步证实了所提出电路的操作。