The gallium-nitride (GaN) high electron-mobility transistor (HEMT) technology has emerged
as an attractive candidate for high-frequency, high-power, and high-temperature …

The progress of wireless communication systems is highly dependent on microwave
technologies. With the escalating adoption of higher frequency bands in communication …

In order to address the challenges of complex process and low precision in traditional
device modeling, double hidden layer back propagation neural network (BPNN) are trained …

Machine learning (ML) has demonstrated significant potential in accelerating the design of
microwave components owing to its great ability to approximate the projection between …

The proficient management and supervision of thermal conditions in microelectronic
equipment are becoming progressively challenging owing to the imposition of heightened …

This paper introduces a deep reinforcement learning approach for optimizing network-on-
chip layout verification and route optimization. The proposed method addresses the …

In this article, we propose the application of a 2-D spectral transposed convolutional neural
network (S-TCNN) with extrapolation to reduce the number of trainable parameters during …

on-chip interconnects are very important in both integrated circuits and systems, affecting
signal transmission directly. To design the interconnects with better performance, designers …

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

We present an open-source database of superconducting quantum device designs that may
be used as the starting point for customized devices. Each design can be generated …