ANALYSIS, SYNTHESIS, AND DIAGNOSTICS OF ANTENNA ARRAYS THROUGH COMPLEX-VALUED NEURAL NETWORKS

摘要

It is shown in this paper that when artificial neural networks are extended to be complex valued, they can be incorporated as a very powerful and effective tool in the analysis, synthesis, and diagnostics of antenna arrays. Artificial neural networks (ANNs) have demonstrated to be a very useful tool in a wide range of scientific, industrial and business applications. In antenna implementations, they have found several branches to deal with, such as, for example: in antenna arrays, for signal - and power - control; in radar, for targets detection and recognition; in microwave devices, for design and optimization; and even in computational electromagnetics, for reducing the number of operations in some kind of calculations. In antenna array design, several works by Christodoulou, Southall, O'Donnell, and Mailloux (some of them with collaborators) are of concern. The tools presented by those authors are based on real-valued ANNs, which, in principle, are the ones initially defined by the pioneers of that field (the first work about ANNs is attributed to McCullough and Pitts, in a paper dated 1943), Nevertheless, several authors have realized that, when dealing with signal processing or analogous mathematical subjects, it would be desirable for the ANN to be complex valued. As seen in the next sections, CVANNs (complex-valued ANNs) have simpler architectures; consequently, their computations are faster. Besides, the configuration of ANNs so considered become easier to understand from a point of view based on mathematical analogies. In what follows, it is assumed that the reader has some familiarity with the theory of antennas, but little less knowledge about ANNs.