The application of intelligent systems is investigated for the automatic tuning of microwave waveguide filters and the alignment of quadrature-amplitude-modulated (QAM) digital microwave radio equipment. The intelligent techniques include conventional rule-based expert systems as well as a machine-learning system which combines techniques from pattern recognition and adaptive signal processing. These approaches are shown to significantly reduce the time and skill required for manual filter alignment and, in addition, they can readily diagnose both type and magnitude of selected faults in the radio communication equipment. This is accomplished via a set of feature data whose parameters are monitored under fault or misalignment conditions, and the deviations from a good pattern are used to adjust the device under test. The selection of appropriate features and alignment of sixcavity 11 GHz waveguide filters and 16-state QAM digital microwave radio-relay-system equipments are discussed.