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In this paper, a neural network model is proposed which can be used for designing any monopole antenna whose element is square shaped and required to exhibit a wide band characteristics. All the antennas designed using this model shows a wideband response between 4.5 GHz - 5 GHz. This model is prepared using Feed Forward Back Propagation Algorithm. The results given by the prepared model are compared...
Artificial neural networks (ANN) are popular as efficient alternatives to conventional computational models like numerical modeling or analytical methods for RF and Microwave modeling and design[1]. Such models reduce both processing time and analytical complexity resulting in simpler computation process. Thus the technique has greater potential in the analysis of various problems in electromagnetism...
In recent years, electromagnetic simulation has seen many changes with adaptation of tools from other fields like DSP, Artificial Neural Networks, Genetic Algorithm etc. This presentation aims at informing the audience of the applications of Soft-Computing techniques for CAD in the area of Antennas and Propagation. It starts with the application of Artificial Neural Networks in design and analysis...
Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned. This paper presents simple and accurate ANN models for the analysis and synthesis of CPS...
Artificial neural networks (ANNs) have been promising tools for many applications. In recent years, a computer-aided design approach based on ANNs has been introduced to microwave modelling, simulation and optimization. In this work, the characteristics parameters of edge coupled coplanar waveguides (CPWs) have been determined with the use of models. These neural models were trained with LM, BR, QN,...
In this work radial basis function algorithm of artificial neural network has been developed to design the analysis and synthesis model of rectangular and square shape microstrip antenna. Rbf is used to design the parameters of square and rectangular patch antenna. Ann method gives very high computational efficiency as compared to the electromagnetic techniques which is time consuming. Rbf is developed...
OFDM digital communication system is highly frequency sensitive to carrier frequency offset between transmitter and receiver local oscillators, which disturbs orthogonality among carriers. Consequently, the performance of OFDM system is reduced greatly due to inter-carrier-interference (ICI). In this paper, we have presented a novel approach for the frequency offset estimation of the OFDM communication...
This paper presents a radar emitter identification and classification technique based on Fuzzy ART and ARTMAP Neural Networks. The radar emitterpsilas parameters of RF, PW, PRI, Direction of Arrival(DOA) etc., are taken as inputs for the networks. The network is trained with the available data of the emitter types. After training, the network is used to identify the emitter type by applying the parameters...
The cavity model is suitable for analytical solution to Helmholtzpsilas equation of patch antennas. Neural network based solutions are suggested as alternatives to conventional cavity methods for the circular microstrip antenna. A trial solution of the differential equation is developed incorporating the boundary conditions. Then the network is trained to satisfy the differential equation.
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