Patnaik, A., Anagnostou, D.E. and Christodoulou, C.G. (2004) Applications of Neural Networks in Wireless Communications. IEEE Antennas and Propagation Magazine, 46, 130-137.
http://dx.doi.org/10.1109/MAP.2004.1374125

has been cited by the following article:

• TITLE: Grating Lobe Suppression with Element Count Optimization in Planar Antenna Array

  AUTHORS: B. Rama Sanjeeva Reddy, D. Vakula

  KEYWORDS: Rectangular Lattice (RL), Triangular Lattice (TL), Element Pattern (EP), Artificial Neural Network (ANN)

  JOURNAL NAME: Journal of Electromagnetic Analysis and Applications, Vol.7 No.2, February 26, 2015

  ABSTRACT: The novel approach of this paper describes the suppression of grating lobe level with the element count optimization in planar antenna array. Rectangular lattice (RL) and triangular lattice (TL) structures are chosen for determining the achievable array element patterns (EP) and further suppressing the grating lobe level. The element spacing and number of elements (10 × 20 array) are taken into account for particular lattice. Grating lobe peaks are observed for the 200-element planar array at maximum scan angle (θ) with the set frequency of 3 GHz. Further, it is found that 14°; bore sight elevation of rectangular lattice produces a transformed field of view, which permits a reduction in element count of 20.39% compared with 10° bore sight elevation. Finally, the typical values of elevation, element count and array size (25 cm2) are trained using artificial neural network (ANN) algorithm and element count is predicted after testing the network. The network shows a high success rate.