In this article, a simple, accurate, fast, and reliable black-box modeling is proposed for the scattering (S)-parameters and noise (N)-parameters of microwave transistors using the general regression neural network (GRNN) with the substantially reduced measurements and computational cost. In this modeling method, GRNN is employed as a nonlinear extrapolator to generalize the S-data and N-data belonging to only a single bias voltage in the middle region into the entire device operation domain of the bias condition (V DS /V CE , I DS /I C , f) within the shortened human effort. The proposed method is implemented to the modeling of the two transistors BFP640 and ATF-551 M4 as study cases. Thus, comparisons are made with the multilayer perceptrons, trained by the two standard backward propagation algorithms, which are the Levenberg-Marquardt, Bayesian regularization and the 10 data mining methods recently published in the literature using the chosen training data sets in both ınterpolation and extrapolation types of generalization. All the comparisons are achieved using four criteria commonly used in the literature. It can be concluded that GRNN is found to be a fast and accurate modeling method that extrapolates the reduced amount of training data consisting of measured S-parameters and N-parameters at the typical currents of the middle bias voltage to the wide operating range.

The performance characterisation of a microwave transistor is carried out rigorously based on the linear circuit and noise theories, subject to the maximum output power and the predetermined input termination. For this purpose, the transducer gain G T is maximised analytically with respect to the input termination Z S for the output port matched, provided that Z S meets the noise figure requirement F req ≥ F min remaining within the unconditionally stable working area (USWA). Analysis is made in the z-parameter domain which facilitates a single unique crescent conditional stability configuration to replace the eight different, rather complicated stability configurations in the S-parameter domain. Finally, the compromise relations between the gain, noise figure for the output port matched are obtained with typical design configurations depending on the operation conditions of a selected high technology transistor. Incompatible noise and gain requirements can also be observed in their design configurations. Furthermore the cross-relations among the bias condition (V DS , I DS) and ingredients of the performance {F req ≥ F min , V out =1, G T ≤ G Tmax } triplets and together with their terminations {Z S , Z L = Z* out (Z S)} can be formed basis for "Performance Data Sheets" of microwave transistors to be employed for the amplifier designs of maximum output power and low noise.

Abstract. In this work, an accurate and reliable S-and Noise (N) -parameter black-box models for a microwave

In this work, a simple, efficient and multi objective Honey Bee Mating Optimization (HBMO) is presented for the performance characterization of a microwave transistor to deliver maximum power to the load with the required noise F req . Thus all the possible compatible {F req ≥ F min , V out = 1, G Tmax } triplets and the corresponding source Z S and load Z L = Z * out (Z S ) terminations can be obtained in the device operation domain of (V DS , I DS and f) without working analytically for the nonlinear performance and stability equations. HBMO is a recently emerging metaheuristic algorithm that combines the powers of the simulated annealing and genetic algorithms. Here, a microwave transistor is chosen as a case study, effectiveness and efficiency of the HBMO are shown by comparing its performance to those of the standard meta-heuristics Genetic and Particle Swarm algorithms and the mean cost results for 10 runs are found to be 0.22, 1.65 and 1.85, respectively, for the comparable execution times. Furthermore, all the numerical results are found to agree with their analytical counterparts obtained using the microwave, linear circuit and noise theories. The Feasible Design Target Space FDTS can be built by the cross relations among all the possible compatible {F req ≥ F min , V out = 1, G Tmax } triplets together their terminations {Z S , Z L = Z * out (Z S )} covering all the possible amplifier designs where both noise figure and output power are at a premium. Copyright

In this work, realizations of a dual function integrated modules are simply built by fixing the identical frequency selective surface (FSS) s into the apertures of the available exponentially tapered transverse electromagnetic (TEM) and ridged horn antennas. Both modules are confirmed experimentally to have functions of prefiltering suppressing EMI and noise when the signal is received, alongside the enhanced directivity in the desired band, thus these modules can be called as "Filtennas." A FSS is simply built by the properly designed periodic double anchor-shaped microstrip patches in CST microwave suit using low-cost FR4 with the relative permittivity 4.4, thickness 1.58 mm, loss tangent 0.0035. From the measured results, it can be found that the proposed modules keep mismatching characteristics of the horn antennas, meanwhile their gains and beamwidths are enhanced to amplify the signal in the desired band and simultaneously deteriorated to attenuate EMI and noise in the out-band. It is expected that this methodology can be implemented to effectively reduce volume and cost of communication systems. V C 2016 Wiley Periodicals, Inc. Int J RF and Microwave CAE 26:287-293, 2016.