This article presents an overview of artificial neural network (ANN) techniques for a
microwave computer-aided design (CAD). ANN-based techniques are becoming useful for …

Depression is a kind of emotion that negatively impacts people's daily lives. The number of
people suffering from long-term feelings is increasing every year across the globe …

In order to model high-speed nonlinear circuits, recurrent neural network (RNN) has been
widely used in computer-aided design (CAD) area to achieve high performance and fast …

In this article, a new technique for macromodeling of high-frequency circuits and
components called high-order deep recurrent neural network (HODRNN) is proposed. This …

This paper deals with the development of a Machine Learning (ML)-based regression for the
construction of complex-valued surrogate models for the analysis of the frequency-domain …

In this paper, a novel method is presented for dynamic behavioral modeling of nonlinear
circuits. The proposed adjoint recurrent neural network (ARNN) model is an extension of the …

This paper proposes a hybrid approach combining Recurrent Neural Network (RNN) and
polynomial regression methods for time-domain modeling of nonlinear circuits. The …

Recurrent neural networks (RNN) emerged as powerful tools to model and analyze the
nonlinear behavior of electronic circuits accurately and quickly. Efforts to improve the …

The nonlinear inverted pendulum model of a lightweight bipedal robot is identified in real-
time using a reservoir-based Recurrent Neural Network (RNN). The adaptation occurs …

In this paper, for the first time, the deep gated recurrent unit (Deep GRU) is used as a new
macromodeling approach for nonlinear circuits. Similar to Long Short-Term Memory (LSTM) …