Guest editorial for the special issue on linear and nonlinear modeling of GaN transistors and circuits

Abstract

SummaryThis Special Issue reviews the state-of-the-art and new trends in modeling of Gallium Nitride transistors. Aspects of transistor characterization, simulation, and design all receive significant attention, highlighting the potential of this disruptive technology in the development of future communication systems. KEYWORDSfield-effect transistors, Gallium Nitride transistors, linear and nonlinear measurements, microwave amplifiers, semiconductor device modelingThe future and success of new communication systems and services (eg, internet of things and long-term evolution) critically depends on the improvement of current and development of new technologies capable of supporting innovative uses of the frequency spectrum under increasingly stringent power constraints. This special issue is dedicated to one of the most important enabling microwave communication technologies of the past 2 decades: Gallium Nitride (GaN). Throughout the years, GaN has been a dominant force in supporting demanding new applications, oftentimes conquering fields once served by entrenched competing technologies (eg, Gallium Arsenide and laterally diffused metal oxide semiconductor). From Very High Frequency (VHF) to E-band systems, GaN relentlessly proves its vast potential for overcoming technological barriers and opening up new territories. [1][2][3] This special issue reports on the state-of-the-art, current challenges, and future prospects in the field of GaN transistor modeling. With the aim of ensuring a comprehensive treatment of the topic, different modeling techniques are addressed. In particular, physics-based numerical models 4 that provide a clear understanding of the most essential physical mechanisms that govern a device's operation, and compact models (eg, equivalent-circuit and behavioral descriptions) that permit the cost-effective design of advanced microwave circuits under nonlinear 5-9 and linear 10-13 operation, receive significant attention. Without a doubt, this special issue demonstrates the fundamental and unique role GaN transistor modeling plays in the conceptual development and design of new communication systems.In addition to the aforementioned topics, significant emphasis also is placed on state-of-the-art measurement techniques.14,15 Indeed, accurate model extraction necessitates the operation of transistors under realistic conditions that depend on the targeted application (eg, amplifier, mixer, and switch) as well as the investigation of device performance under operating conditions (eg, pulsed-bias) capable of exposing nonideal trends and behaviors that have to be accurately accounted for (eg, thermal and trapping effects). Sprinkled throughout the special issue, the reader will find interesting hints as to how advanced nonlinear models can be successfully adopted for designing novel microwave circuits. I would like to extend my gratitude and appreciation to all of the authors for their high quality contributions and to all of the reviewers for devoting their valuable time and expertise to improving ...

RPE Algorithm of Recurrent Neural Network and Its Application In Modeling of Nonlinear Dynamic Systems

“…(3)Algorithm of RNN There are many algorithms for RNNs, and there are currently five basic algorithms, namely: error-correction learning algorithm, memory-based learning algorithm, Herb-type learning algorithm, competitive learning algorithm, and Boltzmann learning algorithm [12][13]. Among them, the error-correction learning algorithm is applied the most, so this article mainly discusses the error-correction learning algorithm of the RNN.…”