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Performance simulation studies for a class of 'smart', conformal array antenna architectures

机译:一类“智能”,保形阵列天线架构的性能仿真研究

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Numerical comparisons between Radial Basis Function Neural Networks (RBFNN) and Linearly Constrained Least Square Method (LCLSM) are investigated for azimuth plane beamsteering for an array of axial sources about a PEC circular cylinder. The results show reasonably good agreement in pattern predictions for the two cases. The preliminary results suggest that the RBFNN can be a promising technique for practical realization of Digital BeamForming for adaptive, phased arrays on conformal surfaces.
机译:径向基函数神经网络(RBFNN)和线性约束最小二乘法(LCLSM)之间的数值比较对围绕PEC圆筒的轴向源阵列的方位角平面光束开始。结果表明两种情况的模式预测相当良好的一致性。初步结果表明,RBFNN可以是用于实际实现用于适应性的适应性分阶段阵列的数字波束形成的有希望的技术。

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