Concurrent Neuro-Fuzzy Systems for Resonant Frequency Computation of Rectangular, Circular, and Triangular Microstrip Antennas

Abstract

Abstract-A method based on concurrent neuro-fuzzy system (CNFS) is presented to calculate simultaneously the resonant frequencies of the rectangular, circular, and triangular microstrip antennas (MSAs).The CNFS comprises an artificial neural network (ANN) and an adaptive-network-based fuzzy inference system (ANFIS). In a CNFS, neural network assists the fuzzy system continuously (or vice versa) to compute the resonant frequency. The resonant frequency results of CNFS for the rectangular, circular, and triangular MSAs are in very good agreement with the experimental results available in the literature.

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

“…But having individual neural model for each performance parameter becomes sometimes unattractive to include in modern antenna computer-aided-design (CAD) programs. It has recently been overcome by introducing 2 ISRN Electronics the concept of generalized neural approach for computing different performance parameters, simultaneously [17][18][19][20]. The resonance frequencies of rectangular, circular, and triangular MSAs have been computed [17][18][19] using generalized neural networks model.…”

“…It has recently been overcome by introducing 2 ISRN Electronics the concept of generalized neural approach for computing different performance parameters, simultaneously [17][18][19][20]. The resonance frequencies of rectangular, circular, and triangular MSAs have been computed [17][18][19] using generalized neural networks model. The resonance frequencies and the physical dimensions of the rectangular MSAs have been computed using generalized neural networks model [20].…”

Adaptive network-based inference system models on multiband patch antenna design

“…ANFIS applications in the field of radio frequency (RF) antenna modeling have been widely applied during the last decade. The resonant frequency computation and synthesis of electrically thin and thick microstrip antennas [10,11], input resistance [12], bandwidth, and resonant frequency computation of various microstrip antennas were studied in the literature [13][14][15].…”

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

“…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. Few other neural models have been proposed for slot loaded microstrip patch antennas in [19,20].…”