we introduced the IEBA and IQA algorithms and discussed their convergence properties. In addition, it was shown a linear operator updates the IEBA state, while that of the IQA is updated nonlinearly. The linearity of the IEBA causes one to recognize the divergency of the IEBA within its execution.We have employed the algorithms to solve 2D TM scattering problems. The numerical examples presented in this article and several other examples illustrate the IEBA and IQA are convergent and fast for the practical low-frequency applications (induction frequency range). In such applications, the IQA presents remarkable rate of convergence in comparison with the HOGEBA and it yields sufficient accuracy for 3-6 iterations. As the frequency is increased, the IEBA and IQA tend to become divergent. However, the IQA is convergent for wider range of frequency, object size, and object contrast. Also, the convergence rate of the IQA is superior to that of the HOGEBA for many cases and in overall; the IQA seems to be an efficient and accurate alternative to the high-order approximations.Our formula should be assessed with incorporation of other approximations, such as the tensor version of QA [3] and the DTA [9]. Furthermore, all algorithms should be implemented not only for 2D TM cases but also for 2D TE and 3D scattering problems. Then, a comparative study is conducted to find out the advantages and drawbacks of the algorithms. This is our future work. -3]. Accurate largesignal model for multi-cell high power HBT devices is of great importance in designing circuits such as power amplifiers where several cells are used at the output stage to deliver the required amount of power. The on-wafer characterization of high power active devices is laborious [4] and has limited accuracy in measuring RF performances such as power gain. This is mainly due to the elevated junction temperature of such devices when biased with high voltages. In addition, commonly used lumped model does not accurately predict the small-signal characteristics of multi-cell HBTs, particularly at higher frequencies where the equivalent electrical circuit of such devices exhibits a distributed nature [5,6]. As reported in [7][8][9][10], small-size HBTs (low power devices) can be easily characterized, and the lumped equivalent circuit is adequate to predict their small-signal characteristics over extended frequency ranges. High-power HBTs are usually composed of several identical elementary cells connected in parallel.Each of these cells can be considered as a small-size HBT and consequently can be modeled by a lumped equivalent circuit. Therefore, it is more appropriate to derive the multi-cell HBT model by scaling up the elementary-cell device model. CHARACTERIZED HBT DEVICESTwo GaAsHBT devices were characterized to illustrate in detail the proposed modeling approach. The first device is a small-size GaAsHBT (HBT1) composed of an elementary-cell ( Fig. 1). The second device is a large-size GaAsHBT (HBT2) composed of three cells (Fig. 2). Figure 1 shows the physi...

The time or frequency at which the electromagnetic (EM) response of a buried inhomogeneity can first be measured is determined by its depth of burial and the average conductivity of the overlying section; it is relatively independent of the type of source or receiver and their separation. The ability to make measurements at this time or frequency, however, depends on the sensitivity and accuracy of the instrumentation, the signal strength, and the ambient noise level. These factors affect different EM sounding systems in surprisingly different ways. For the magnetotelluric (MT) method, it is possible to detect a buried half‐space under about 1.5 skin depths of overburden. The maximum depth of investigation is virtually unbounded because of high signal strengths at low frequencies. Transient electromagnetic (TEM) soundings, on the other hand, have a limited depth of penetration, but are less affected by static shift errors. For TEM, a buried inhomogeneity can be detected under about one diffusion depth of overburden. For conventional near‐zone sounding in which induced voltage is measured (impulse response), the depth of investigation is proportional to the [Formula: see text] power of the source moment and ground resistivity. By contrast, if the receiver is a magnetometer (step response system), the depth of investigation is proportional to the [Formula: see text] power of source moment and is no longer a function of resistivity. Magnetic‐field measurements may, therefore, be superior for exploration in conductive areas such as sedimentary basins. Far‐zone, or long‐offset, TEM soundings are traditionally used for deep exploration. The depth of investigation for a voltage receiver is proportional to the [Formula: see text] power of source moment and resistivity and is inversely proportional to the source‐receiver separation. Magnetic‐field measurements are difficult to make at long offsets because instrumental accuracy limits the measurement of the very slow decay of the magnetic field. Frequency‐domain controlled‐source systems are ideally suited for sounding at the very shallow depths needed for engineering, archaeological, and groundwater applications because of the relative ease of extending the measurements to arbitrarily high frequencies, and also because geometric soundings can be made at low induction numbers.

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Problems and misunderstandings arise with the concept of apparent resistivity when the analogy between an apparent resistivity computed from geophysical observations and the true resistivity structure of the subsurface is drawn too tightly. Several definitions of apparent resistivity are available for use in electromagnetic methods; however, those most commonly used do not always exhibit the best behavior. Many of the features of the apparent resistivity curve which have been interpreted as physically significant with one definition disappear when alternative definitions are used. It is misleading to compare the detection or resolution capabilities of different field systems or configurations solely on the basis of the apparent resistivity curve. For the in‐loop transient electromagnetic (TEM) method, apparent resistivity computed from the magnetic field response displays much better behavior than that computed from the induced voltage response. A comparison of “exact” and “asymptotic” formulas for the TEM method reveals that automated schemes for distinguishing early‐time and late‐time branches are at best tenuous, and those schemes are doomed to failure for a certain class of resistivity structures (e.g., the loop size is large compared to the layer thickness). For the magnetotelluric (MT) method, apparent resistivity curves defined from the real part of the impedance exhibit much better behavior than curves based on the conventional definition that uses the magnitude of the impedance. Results of using this new definition have characteristics similar to apparent resistivity obtained from time‐domain processing.