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In this paper, a new neuro-based approach using a feed-forward neural network is presented to design a Wilkinson power divider. The proposed power divider is composed of symmetrical modified T-shaped resonators, which are a replacement for quarter-wave transmission lines in the conventional structure.The proposed technique reduces the size of the power divider by 45% and suppresses unwanted bands up to the fifth harmonics. To verify the concept, a prototype of the power divider has been fabricated and tested, exhibiting good agreement between the predicted and measured results. The results show that the insertion loss and the isolation at the center frequency are about 3.3 ± 0.1 dB and 23 dB, respectively. K E Y W O R D Sartificial intelligence, couplers, evolutionary optimization, harmonic suppression, lumpedequivalent circuit, microstrip technology, neural network, Wilkinson power divider

A novel microstrip low‐pass filter is presented to achieve an ultra‐wide stopband with 11 harmonic suppression and very sharp skirt characteristics. The filter is composed of a modified U‐shaped resonator (which creates two fully adjustable transmission zeroes), a T‐shaped resonator (which determines a cut‐off frequency), and four radial stubs (which provide a wider stopband). The operating mechanism of the filter is investigated based on a proposed equivalent‐circuit model, and the role of each section of the proposed filter in creating null points is theoretically discussed in detail. The presented filter with 3 dB cut‐off frequency (fc=2.35 GHz) has been fabricated and measured. Results show that a relative stopband bandwidth of 164% (referred to as a 22 dB suppression) is obtained while achieving a high figure‐of‐merit of 15,221.