Abstract: In order to obtain a high step-up voltage gain, high-efficiency converter, this paper proposed a dual switches dc/dc converter with three-winding-coupled inductor and charge pump. The ...

Abstract: In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear systems ...

Abstract: Convolutional Neural Network (CNN) models are a type of deep learning architecture introduced to achieve the correct classification of breast cancer. This paper has a two-fold purpose. The ...

Abstract: Recently, deep-learning-based fault diagnosis methods have been widely studied for rolling bearings. However, these neural networks are lack of interpretability for fault diagnosis tasks.

We report GaN p-n diodes on free-standing GaN substrates: a record high Baliga's figure-of-merit (V<;sub>B<;/sub><;sup>2<;/sup>/ Ron) of ...

Abstract: In spite of the increasing use of machine learning techniques, in-memory computing and hardware have increased the interest to accelerate neural network operation. Henceforth, novel embedded ...

Abstract: Large Language Models (LLMs) recently demonstrated extraordinary capability in various natural language processing (NLP) tasks including language translation, text generation, question ...

Abstract: As the basis for the static security of the power grid, power load forecasting directly affects the safety of grid operation, the rationality of grid planning, and the economy of ...

Abstract: The regional integration of variable wind power could be restricted by a strong coupling of electric power generation dispatch and heat supply of combined heat-and-power (CHP) units. The ...

Abstract: This letter presents a method for satellite image classification aiming at the following two objectives: 1) involving visual attention into the satellite image classification; biologically ...

Abstract: Economic dispatch is a critical problem in operation of power grids. A consensus-based algorithm was recently proposed to solve the economic dispatch problem in a distributed manner. In this ...

Abstract: Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure proper ...