Fuzzy associative memories for the computation of the bandwidth of rectangular microstrip antennas with thin and thick substrates

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

“…However, in [51,52], more outputs were calculated by using multiple ANFIS. In general, in the literature, each different parameter of each different MSA was computed by using a different individual ANN [53][54][55] or ANFIS model [56][57][58][59][60]. Single neural models were proposed in [61,62] for simultaneously calculating the resonant frequencies of the rectangular, circular, and triangular MSAs.…”

Computation of resonant frequency for equilateral triangular microstrip antennas using the adaptive neuro-fuzzy inference system

“…We also proposed FISs [35,36] and ANNs [37][38][39][40][41][42][43][44][45] to calculate accurately the various parameters of the rectangular and circular MSAs. In [35,36], the classical, modified, and improved tabu search algorithms were used to determine optimally the design parameters of the FISs. Simple formulas for the resonant frequencies of rectangular and circular MSAs were also presented in [46 -50].…”

Particle Swarm Optimization-Based Rectangular Microstrip Antenna Designing

“…The 6 data sets, marked with an asterisk in Table 5, were used for testing. The training and test data sets used in this paper are also the same as those used for ANNs [19,15] and FISs [20]. The antennas given in Table 5 vary in electrical thickness from 0.0065 to 0.2284, and in physical thickness from 0.17 to 12.81 mm, and operate over the frequency range 2.980-8.000 GHz.…”