Small-signal modeling and parameter extraction method for a multigate GaAs pHEMT switch

This paper presents an accurate small-signal model for multi-gate GaAs pHEMTs in switching-mode.The extraction method for the proposed model is developed.A 2-gate switch structure is fabricated on a commercial 0.5μm AlGaAs/GaAs pHEMT technology to verify the proposed model.Excellent agreement has been obtained between the measured and simulated results over a wide frequency range.

A Direct Parameter-Extraction Method for GaInP/GaAs Heterojunction Bipolar Transistors Small-Signal Model

An accurate and broad-band method for hetero-junction bipolar transistors(HBT) small-signal model parameters-extraction is presented in this paper. An equivalent circuit forthe HBT under a forward-bias condition is proposed for extraction of accessresistance and parasiticinductance. This method differs from previous ones by extracting the c-quivalent circuit parameterswithout using special test structure or global numerical optimization techniques. The mainadvantage of this method is that a unique and physically meaningful set of intrinsic parameters isextracted from impedance and admittance representation of the measured S-pa-rameters in thefrequency range of 1-12 GHz under different bias conditions. The method yields a deviation of lessthan 5% between measured and modeled S-parameters.

Small-signal modeling of GaN HEMT switch with a new intrinsic elements extraction method

A novel and accurate method is proposed to extract the intrinsic elements of the GaN high-electron-mobility transistor（HEMT） switch.The new extraction method is verified by comparing the simulated S-parameters with the measured data over the 5-40 GHz frequency range.The percentage errors E（ij） within 3.83% show the great agreement between the simulated S-parameters and the measured data.

Small-signal modelling and stability analysis of grid-following and grid-forming inverters dominated power system

In this paper,the explicit state-space model for a multi-inverter system including grid-following inverter-based generators(IBGs)and grid-forming IBGs is developed by the two-level component connection method(CCM),which modularized inverter control blocks at the primary level and IBGs at the secondary level.Based on the comprehensive state-space model representing full order of system dynamics,eigenvalues of the overall system are thoroughly analyzed,identifying potential adverse impacts of not only grid-following inverters,but also grid forming inverters on the system small-signal stability,with the underlying principle of oscillations also understood.Numerical and simulation results validate effectiveness of the proposed methodology on IEEE benchmarking 39-bus system.

A novel small-signal equivalent circuit model for GaN HEMTs incorporating a dual-field-plate

An accurate and novel small-signal equivalent circuit model for GaN high-electron-mobility transistors(HEMTs)is proposed,which considers a dual-field-plate(FP)made up of a gate-FP and a source-FP.The equivalent circuit of the overall model is composed of parasitic elements,intrinsic transistors,gate-FP,and source-FP networks.The equivalent circuit of the gate-FP is identical to that of the intrinsic transistor.In order to simplify the complexity of the model,a series combination of a resistor and a capacitor is employed to represent the source-FP.The analytical extraction procedure of the model parameters is presented based on the proposed equivalent circuit.The verification is carried out on a 4×250μm GaN HEMT device with a gate-FP and a source-FP in a 0.45μm technology.Compared with the classic model,the proposed novel small-signal model shows closer agreement with measured S-parameters in the range of 1.0 to 18.0 GHz.

Small-Signal Equivalent Circuit Modeling of a Photodetector Chip

A small-signal equivalent circuit model and the ted. The equivalent lumped circuit, which takes the main extraction techniques for photodetector chips are presen- factors that limit a photodetector＇s RF performance into consideration,is first determined based on the device＇s physical structure. The photodetector＇s S parameters are then on-wafer measured, and the measured raw data are processed with further calibration. A genetic algorithm is used to fit the measured data, thereby allowing us to calculate each parameter value of the model. Experimental resuits show that the modeled parameters are well matched to the measurements in a frequency range from 130MHz to 20GHz, and the proposed method is proved feasible. This model can give an exact description of the photodetector chip＇s high frequency performance,which enables an effective circuit-level prediction for photodetector and optoelectronic integrated circuits.

Design of InAlAs/InGaAs PHEMTs and small-signal modeling from 0.5 to 110 GHz

90-nm T-shaped gate InP-based In_（0.52）Al_（0.48）As/In_（0.6）Ga_（0.4）As pseudomorphic high electron mobility transistors were designed and fabricated with a gate-width of 2×30 μm,a source-drain space of 2.5 μm,and a source-gate space of 0.75 μm.DC,RF and small-signal model characterizations were demonstrated.The maximum saturation current density was measured to be 755 mA/mm biased at V_（gs）=0.6 V and V_（ds）=1.5 V.The maximum extrinsic transconductance was measured to be 1006 mS/mm biased at V_（ds）=—0.1V and V_（ds）=1.5 V.The extrapolated current gain cutoff frequency and maximum oscillation frequency based on S-parameters measured from 0.5 to 110 GHz were 180 and 264 GHz,respectively.The inflection point（the stability factor k=1）where the slope from-10 dB/decade（MSG） to-20 dB/decade（MAG） was measured to be 83 GHz.The smallsignal model of this device was also established,and the S-parameters of the model are consistent with those measured from 0.5-110 GHz.

A new small-signal model for asymmetrical AlGaN/GaN HEMTs

A new small-signal model for anisomerous AlGaN/GaN high electron mobility transistors（HEMTs） is proposed for accurate prediction of HEMT behavior up to 20 GHz.The parasitic elements are extracted from both cold-FET and pinch-off bias to obtain more precise results and the intrinsic part is directly extracted.All the parameters needed in this process are determined by the device structure rather than optimization methods.This guarantees consistency between the parameter values and the component＇s physical meaning.

Improvements to the extraction of an AlGaN/GaN HEMT small-signal model

The accurate extraction of AlGaN/GaN HEMT small-signal models, which is an important step in largesignal modeling, can exactly reflect the microwave performance of the physical structure of the device. A new method of extracting the parasitic elements is presented, and an open dummy structure is introduced to obtain the parasitic capacitances. With a Schottky resistor in the gate, a new method is developed to extract Rg. In order to characterize the changes of the depletion region under various drain voltages, the drain delay factor is involved in the output conductance of the device. Compared to the traditional method, the fitting of S 11 and S 22 is improved, and fT and fmax can be better predicted. The validity of the proposed method is verified with excellent correlation between the measured and simulated S-parameters in the range of 0.1 to 26.1 GHz.

Small-signal Model for Dual-active-bridge Converter Considering Total Elimination of Reactive Current

Emerging technologies such as electric vehicles,solid-state transformers,and DC transformers are implemented using the closed-loop bi-directional dual-active-bridge(DAB)converter.In this context,it is necessary to have average models that provide an efficient way of tuning the proportional integral(PI)compensator parameters for large-and small-signal applications.We present a novel small-signal model(SSM)for DAB converter with a single closed-loop PI controller and the total elimination of reactive current(IQ=0).The method applies a modulation technique for IQ=0 and introduces a composite function in the controller while reducing the original nonlinear switching model,which allows to decrease the order of the transfer function and analyze the closed-loop operation.The proposed SSM is analyzed using different response time,load,and DC voltage changes.The simulation and experimental results demonstrate the ease of implementation and effectiveness of the proposed model with respect to other SSM techniques.

A complete small-signal HBT model including AC current crowding effect

An improved small-signal equivalent circuit of HBT concerning the AC current crowding effect is proposed in this paper. AC current crowding effect is modeled as a parallel RC circuit composed of Cbi and Rbi, with distributed base-collector junction capacitance also taken into account. The intrinsic portion is taken as a whole and extracted directly from the measured Sparameters in the whole frequency range of operation without any special test structures. An HBT device with a 2 × 20 μm^(2) emitter-area under three different biases were used to demonstrate the extraction and verify the accuracy of the equivalent circuit.

Extraction of temperature dependences of small-signal model parameters in SiGe HBT HICUM model

In this work, temperature dependences of small-signal model parameters in the SiGe HBT HICUM model are presented. Electrical elements in the small-signal equivalent circuit are first extracted at each temperature, then the temperature dependences are determined by the series of extracted temperature coefficients, based on the established temperature for- mulas for corresponding model parameters. The proposed method is validated by a 1x 0.2 x 16 μm2 SiGe HBT over a wide temperature range （from 218 K to 473 K）, and good matching is obtained between the extracted and modeled resuits. Therefore, we believe that the proposed extraction flow of model parameter temperature dependence is reliable for characterizing the transistor performance and guiding the circuit design over a wide temperature range.

Modeling and small-signal stability analysis of doubly-fed induction generator integrated system

Owing to their stability,doubly-fed induction generator(DFIG)integrated systems have gained considerable interest and are the most widely implemented type of wind turbines and due to the increasing escalation of the wind generation penetration rate in power systems.In this study,we investigate a DFIG integrated system comprising four modules:(1)a wind turbine that considers the maximum power point tracking and pitch-angle control,(2)induction generator,(3)rotor/grid-side converter with the corresponding control strategy,and(4)AC power grid.The detailed small-signal modeling of the entire system is performed by linearizing the dynamic characteristic equation at the steady-state value.Furthermore,a dichotomy method is proposed based on the maximum eigenvalue real part function to obtain the critical value of the parameters.Root-locus analysis is employed to analyze the impact of changes in the phase-locked loop,short-circuit ratio,and blade inertia on the system stability.Lastly,the accuracy of the small-signal model and the real and imaginary parts of the calculated dominant poles in the theoretical analysis are verified using PSCAD/EMTDC.

Small-signal model parameter extraction for microwave SiGe HBTs based on Y- and Z-parameter characterization

High frequency intrinsic small-signal model parameter extraction for microwave SiGe heterojunction bipolar transistors is studied, with a focus on the main feedback elements including the emitter series resistor, internal and external base-collector capacitors as well as the base series resistor, all of which are important in determining the behavior of the device equivalent circuit. In accordance with the respective features of definition of the Y- and Z-parameters, a novel combined use of them succeeds in reasonably simplifying the device equivalent circuit and thus decoupling the extraction of base-collector capacitances from other model parameters. As a result, a very simple direct extraction method is proposed. The proposed method is applied for determining the SiGe HBT small-signal model parameters by taking numerically simulated Y- and Z-parameters as nominal ＂measurement data＂ with the help of a Taurus-device simulator. The validity of the method is preliminarily confirmed by the observation of certain linear relations of device frequency behavior as predicted by the corresponding theoretical analysis. Furthermore, the extraction results can be used to reasonably account for the dependence of the extracted model parameters on device geometry and process parameters, reflecting the explicit physical meanings of parameters, and especially revealing the distributed nature of the base series resistor and its complex interactions with base-collector capacitors. Finally, the accuracy of our model parameter extraction method is further validated by comparing the modeled and simulated S-parameters as a function of frequency.

Small-signal model parameter extraction for AlGaN/GaN HEMT

A new 22-element small signal equivalent circuit model for the AlGaN/G N high electron mobility transistor（HEMT） is presented. Compared with the traditional equivalent circuit model, the gate forward and breakdown conductions（G_（gsf） and G_（gdf）） are introduced into the new model to characterize the gate leakage current. Additionally, for the new gate-connected field plate and the source-connected field plate of the device, an improved method for extracting the parasitic capacitances is proposed, which can be applied to the small-signal extraction for an asymmetric device. To verify the model, S-parameters are obtained from the modeling and measurements. The good agreement between the measured and the simulated results indicate that this model is accurate,stable and comparatively clear in physical significance.

Aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders:progress of experimental models based on disease pathogenesis

Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism remains unknown.Therefore,experimental models of neuromyelitis optica spectrum disorders are essential for exploring its pathogenesis and in screening for therapeutic targets.Since most patients with neuromyelitis optica spectrum disorders are seropositive for IgG autoantibodies against aquaporin-4,which is highly expressed on the membrane of astrocyte endfeet,most current experimental models are based on aquaporin-4-IgG that initially targets astrocytes.These experimental models have successfully simulated many pathological features of neuromyelitis optica spectrum disorders,such as aquaporin-4 loss,astrocytopathy,granulocyte and macrophage infiltration,complement activation,demyelination,and neuronal loss;however,they do not fully capture the pathological process of human neuromyelitis optica spectrum disorders.In this review,we summarize the currently known pathogenic mechanisms and the development of associated experimental models in vitro,ex vivo,and in vivo for neuromyelitis optica spectrum disorders,suggest potential pathogenic mechanisms for further investigation,and provide guidance on experimental model choices.In addition,this review summarizes the latest information on pathologies and therapies for neuromyelitis optica spectrum disorders based on experimental models of aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders,offering further therapeutic targets and a theoretical basis for clinical trials.

Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

Global Piecewise Analysis of HIV Model with Bi-Infectious Categories under Ordinary Derivative and Non-Singular Operator with Neural Network Approach

This study directs the discussion of HIV disease with a novel kind of complex dynamical generalized and piecewise operator in the sense of classical and Atangana Baleanu(AB)derivatives having arbitrary order.The HIV infection model has a susceptible class,a recovered class,along with a case of infection divided into three sub-different levels or categories and the recovered class.The total time interval is converted into two,which are further investigated for ordinary and fractional order operators of the AB derivative,respectively.The proposed model is tested separately for unique solutions and existence on bi intervals.The numerical solution of the proposed model is treated by the piece-wise numerical iterative scheme of Newtons Polynomial.The proposed method is established for piece-wise derivatives under natural order and non-singular Mittag-Leffler Law.The cross-over or bending characteristics in the dynamical system of HIV are easily examined by the aspect of this research having a memory effect for controlling the said disease.This study uses the neural network(NN)technique to obtain a better set of weights with low residual errors,and the epochs number is considered 1000.The obtained figures represent the approximate solution and absolute error which are tested with NN to train the data accurately.

Prognostic model for esophagogastric variceal rebleeding after endoscopic treatment in liver cirrhosis: A Chinese multicenter study

BACKGROUND Rebleeding after recovery from esophagogastric variceal bleeding(EGVB)is a severe complication that is associated with high rates of both incidence and mortality.Despite its clinical importance,recognized prognostic models that can effectively predict esophagogastric variceal rebleeding in patients with liver cirrhosis are lacking.AIM To construct and externally validate a reliable prognostic model for predicting the occurrence of esophagogastric variceal rebleeding.METHODS This study included 477 EGVB patients across 2 cohorts:The derivation cohort(n=322)and the validation cohort(n=155).The primary outcome was rebleeding events within 1 year.The least absolute shrinkage and selection operator was applied for predictor selection,and multivariate Cox regression analysis was used to construct the prognostic model.Internal validation was performed with bootstrap resampling.We assessed the discrimination,calibration and accuracy of the model,and performed patient risk stratification.RESULTS Six predictors,including albumin and aspartate aminotransferase concentrations,white blood cell count,and the presence of ascites,portal vein thrombosis,and bleeding signs,were selected for the rebleeding event prediction following endoscopic treatment(REPET)model.In predicting rebleeding within 1 year,the REPET model ex-hibited a concordance index of 0.775 and a Brier score of 0.143 in the derivation cohort,alongside 0.862 and 0.127 in the validation cohort.Furthermore,the REPET model revealed a significant difference in rebleeding rates(P<0.01)between low-risk patients and intermediate-to high-risk patients in both cohorts.CONCLUSION We constructed and validated a new prognostic model for variceal rebleeding with excellent predictive per-formance,which will improve the clinical management of rebleeding in EGVB patients.