Neural networks are electronic systems which can be trained toremember behavior of a modeled structure in given operational points,and which can be used to approximate behavior of the structure out ofthe training points. These approximation abilities of neural nets aredemonstrated on modeling a frequency-selective surface, a microstriptransmission line and a microstrip dipole. Attention is turned to theaccuracy and to the efficiency of neural models. The association ofneural models and genetic algorithms, which can provide a global designtool, is discussed
This paper describes an application of the structured genetic algorithm to the construction of micro...
In recent years, evolutionary algorithms have been successfully adopted for the optimization of vari...
In recent years, evolutionary algorithms have been successfully adopted for the optimization of vari...
Neural networks are electronic systems which can be trained to remember behavior of a modeled struct...
Artificial neural networks can be used for modeling microwave structures in order to obtain computat...
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...
An overview of neural network-based modeling techniques and their applications in microwave modeling...
In the paper, an original methodology for the automatic creation of neural models of microwave struc...
Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that ...
In the paper, an original methodology for the automatic creation of neural models of microwave struc...
Abstract. The paper describes the methodology of the automated creation of neural models of microwav...
The paper describes the exploitation of feed-forward neural networks and recurrent neural networks f...
This paper presents a new approach to microwave circuit analysis and optimization featuring neural n...
The application of a multilayer perceptron (MLP) for calculating the electrodynamic characteristics ...
This paper describes an application of the structured genetic algorithm to the construction of micro...
In recent years, evolutionary algorithms have been successfully adopted for the optimization of vari...
In recent years, evolutionary algorithms have been successfully adopted for the optimization of vari...
Neural networks are electronic systems which can be trained to remember behavior of a modeled struct...
Artificial neural networks can be used for modeling microwave structures in order to obtain computat...
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...
An overview of neural network-based modeling techniques and their applications in microwave modeling...
In the paper, an original methodology for the automatic creation of neural models of microwave struc...
Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that ...
In the paper, an original methodology for the automatic creation of neural models of microwave struc...
Abstract. The paper describes the methodology of the automated creation of neural models of microwav...
The paper describes the exploitation of feed-forward neural networks and recurrent neural networks f...
This paper presents a new approach to microwave circuit analysis and optimization featuring neural n...
The application of a multilayer perceptron (MLP) for calculating the electrodynamic characteristics ...
This paper describes an application of the structured genetic algorithm to the construction of micro...
In recent years, evolutionary algorithms have been successfully adopted for the optimization of vari...
In recent years, evolutionary algorithms have been successfully adopted for the optimization of vari...