Abstract—In recent years, Artificial Neural networks (ANNs) have been intensively employed to build smart model of microwave devices. In this paper a characterization of lossy SIW resonators by means of Multilayer Perceptron Neural Networks (MLPNNs) on Graphics Processing Unit (GPU), is presented. Once properly selected and trained, a MLPNN can evaluate the lossy SIW resonator’s resonant frequency fr and the pertaining quality factor Q at a shorter time than the full-wave rigorous model. In this way, fast parametric models of SIW structures to employ for the design and optimization of microwave devices, exploiting the computational power of GPUs, can be obtained. 1
This paper presents a new model based on the backpropagation multilayered perception network to find...
Artificial neural networks (ANNs) have been promising tools for many applications. In recent years, ...
The paper describes the exploitation of feed-forward neural networks and recurrent neural networks f...
Artificial neural networks can be used for modeling microwave structures in order to obtain computat...
An overview of neural network-based modeling techniques and their applications in microwave modeling...
Artificial neural networks (ANNs) are presented for the technology-independent modeling of active de...
This paper presents a new approach to microwave circuit analysis and optimization featuring neural n...
ANN has a wide application areas. One of these applications areas is the optimization of microwave f...
LGEP 2011 ID = 739International audienceThis paper shows that Ridge Polynomial Neural Networks (RPNN...
Abstract — In this paper, we present simulations of a microwave sensor in a cylindrical leaky metall...
Abstract. The paper describes the methodology of the automated creation of neural models of microwav...
In this article, a novel and efficient approach for modeling radio‐frequency microelectromechanical ...
Artificial neural networks (ANNs)are presented for the fast and accurate modeling of passive and act...
Small-signal and noise behaviour of an active microwave device is modeled through the neural network...
Artificial neural networks (ANNs) has been a promising tool for microwave modeling, simulation and o...
This paper presents a new model based on the backpropagation multilayered perception network to find...
Artificial neural networks (ANNs) have been promising tools for many applications. In recent years, ...
The paper describes the exploitation of feed-forward neural networks and recurrent neural networks f...
Artificial neural networks can be used for modeling microwave structures in order to obtain computat...
An overview of neural network-based modeling techniques and their applications in microwave modeling...
Artificial neural networks (ANNs) are presented for the technology-independent modeling of active de...
This paper presents a new approach to microwave circuit analysis and optimization featuring neural n...
ANN has a wide application areas. One of these applications areas is the optimization of microwave f...
LGEP 2011 ID = 739International audienceThis paper shows that Ridge Polynomial Neural Networks (RPNN...
Abstract — In this paper, we present simulations of a microwave sensor in a cylindrical leaky metall...
Abstract. The paper describes the methodology of the automated creation of neural models of microwav...
In this article, a novel and efficient approach for modeling radio‐frequency microelectromechanical ...
Artificial neural networks (ANNs)are presented for the fast and accurate modeling of passive and act...
Small-signal and noise behaviour of an active microwave device is modeled through the neural network...
Artificial neural networks (ANNs) has been a promising tool for microwave modeling, simulation and o...
This paper presents a new model based on the backpropagation multilayered perception network to find...
Artificial neural networks (ANNs) have been promising tools for many applications. In recent years, ...
The paper describes the exploitation of feed-forward neural networks and recurrent neural networks f...