Development of knowledge based artificial neural network models for microwave components

Abstract

number of time-consuming FDTD simulations, leading to a substantial reduction of the total design time.

Estimation of Different Performance Parameters of Slotted Microstrip Antennas with Air-Gap Using Neural Networks

“…Thus, the requirement for having a new solution for every small alteration in the geometry as well as the problems associated with the thickness of the substrates in analytical methods leads to complexities and processing cost [9]. Recently, artificial neural networks (ANNs) models have acquired tremendous applications in the wireless communication due to their ability and adaptability to learn and generalization features [9][10][11][12][13][14][15][16]. The ANN model is trained using measured, calculated or simulated patterns.…”

“…The resonance frequencies and the physical dimensions of the rectangular MSAs have been computed using generalized neural networks model [20]. Hence, the individual neural models [9][10][11][12][13][14][15][16] and generalized neural approaches [17][18][19][20] have been used only for resonance frequency and/or geometric dimensions of microstrip patch antennas. Few neural networks models [21][22][23] have also been proposed for designing the slotted microstrip antennas.…”

“…Few neural networks models [21][22][23] have also been proposed for designing the slotted microstrip antennas. But unfortunately, simultaneous computations of different performance parameters (i.e., resonance frequency, gain, directivity, antenna efficiency, and radiation efficiency) using neural networks model have been rarely attempted in the available literature [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] as these parameters are essentially required for antenna designers for synthesizing the MSAs. In the proposed work, the authors have extended their earlier works of generalized neural networks modeling [24][25][26][27][28][29][30] for predicting different performance parameters (i.e., resonance frequencies, gains, directivities, antenna efficiencies, and radiation efficiencies) of slotted microstrip antennas for dualfrequency operation.…”

Investigations for Performance Improvement of X-Shaped Rmsa Using Artificial Neural Network by Predicting Slot Size

“…The use of ANN in rectangular microstrip patch antenna (RMSA) has been proposed in [5][6][7][8]. Further, Watson et al [9] developed an ANN model for microwave components. Different ANN models [10][11][12][13][14][15][16][17][18] were used for analyzing and synthesizing of microstrip patch antennas.…”

Robust training of microwave neural models

“…These neural models can be used in place of computationally intensive physics/EM models of active/passive devices to speed up microwave design. Neural network modeling techniques have been used for a wide variety of microwave applications such as microstrip interconnects [1,2], vias [3,4], spiral inductors [5], FET devices [1,6], and HBT devices [7]. Neural networks have also been used in circuit simulation and optimization [8], filter design [9], impedance matching [10], and synthesis [11].…”