In this article, we consider designs of simple analog artificial neural networks based on adiabatic Josephson cells with a sigmoid activation function. A new approach based on the gradient descent method is developed to adjust the circuit parameters, allowing efficient signal transmission between the network layers. The proposed solution is demonstrated on the example of the system implementing XOR and OR logical operations.

翻译：本文研究了基于具有S型激活函数的绝热约瑟夫森单元的简单模拟人工神经网络设计。我们提出了一种基于梯度下降法的新方法，用于调整电路参数，从而实现网络层间高效信号传输。以执行XOR与OR逻辑运算的系统为例，对所提解决方案进行了验证。