An integrated multibias extraction technique for MESFET and high electron-mobility transistor (HEMT) models is presented in this paper. The technique uses-parameters measured at various bias points in the active region to construct one optimization problem, of which the vector of unknowns contains a set of bias-dependent elements for each bias point and one set of bias-independent elements. This problem is solved by an extremely robust decomposition-based optimizer, which splits the problem into subproblems, being the number of unknowns. The optimizer consistently converges to the same solution from a wide range of randomly chosen starting values. No assumptions are made concerning the layout of the device or the bias dependencies of the intrinsic model elements. It is shown that there is a convergence in the values of the model elements and a decrease in the extraction uncertainty as the number of bias points in the extraction is increased. Robustness tests using 100 extractions, each using a different set of random starting values, are performed on measured-parameters of a MESFET and pseudomorphic HEMT device. Results indicate that the extracted parameters typically vary by less than 1%. Extractions with up to 48 bias points were performed successfully, leading to the simultaneous determination of 342 model elements.

A recently proposed optimizer-based parameterextraction technique using adaptive decomposition is subjected to a systematic and rigorous evaluation. The technique is shown to be robust and accurate under varying starting conditions. A study of convergence performance based on decomposition theory and test results is presented. Robustness tests are used to show that commonly used statistical descriptions such as mean and standard deviation are inadequate for presenting these types of test data.

Figure 4 Characteristic impedance and dispersion characteristicsfor the dominant and first two higher-order modes of shielded dielectric-loaded edge-coupled CBCPW structure with a = 4 mm, h , = h , = 1 mm, E ,~ = 2.22, and other parameters as in Figure 3 choosing appropriate loading and structural parameters, one can optimize the behavior with respect to isolation, singlemode bandwidth, and uniformity of coupling. ABSTRACT A new method for the entraction of the 13-element GaAs FET model from hot S parameters is presented. The method reduces the uniqueness problem that mists between the parasitic gate resistance R, and the channel resistance K,. Ihirteen error functions are used, with the order of o~~rimiza~ion determined through a principle-components semihi& analysis. 0 ABSTRACT In this work we present a new optical& controlled microwave matching technique. In this technique the gap between two microwave coupled

In this article, the design, fabrication, and testing of a wide band single-ended power amplifier (PA) using GaN field effect transistors (FETs) are reported. The singleended amplifier demonstrates a bandwidth larger than 30% around 2 GHz, with a high gain, PAE, and output power combination.

A new hybrid multibias analytical/decomposition-based parameter extraction procedure for GaAs FETs is described. The analytical calculations are integrated into an existing decomposition-based optimizer in a complementary approach, further increasing the robustness of the existing algorithm. It is illustrated that, in order to increase the reliability with which the full 15-element small-signal model can be extracted, it is necessary to exploit the underlaying characteristics of the system and the measured data used. This is achieved through the use of cold -parameter data, along with simple modifications to the extraction algorithm, and a new intelligent selection algorithm for the active bias points used in the multi-bias extraction. The selection algorithm employs a simple geometric abstraction for the -parameter data that allows it to select bias points that maximize the information available to the extraction procedure. The new selection algorithm shows for the first time what the influence of the bias points is on the performance of a multibias extraction procedure. Experimental results proving the robustness and accuracy of the described procedures are presented.