A review on GaN HEMTs:nonlinear mechanisms and improvement methods

The GaN HEMT is a potential candidate for RF applications due to the high frequency and large power handling capability.To ensure the quality of the communication signal,linearity is a key parameter during the system design.However,the GaN HEMT usually suffers from the nonlinearity problems induced by the nonlinear parasitic capacitance,transconductance,channel transconductance etc.Among them,the transconductance reduction is the main contributor for the nonlinearity and is mostly attributed to the scattering effect,the increasing resistance of access region,the self-heating effect and the trapping effects.Based on the mechanisms,device-level improvement methods of transconductance including the trapping suppression,the nanowire channel,the graded channel,the double channel,the transconductance compensation and the new material structures have been proposed recently.The features of each method are reviewed and compared to provide an overview perspective on the linearity of the GaN HEMT at the device level.

Research on Grid-Connected Control Strategy of Distributed Generator Based on Improved Linear Active Disturbance Rejection Control

The virtual synchronous generator(VSG)technology has been proposed to address the problem of system frequency and active power oscillation caused by grid-connected new energy power sources.However,the traditional voltage-current double-closed-loop control used in VSG has the disadvantages of poor disturbance immunity and insufficient dynamic response.In light of the issues above,a virtual synchronous generator voltage outer-loop control strategy based on improved linear autonomous disturbance rejection control(ILADRC)is put forth for consideration.Firstly,an improved first-order linear self-immunity control structure is established for the characteristics of the voltage outer loop;then,the effects of two key control parameters-observer bandwidthω_(0)and controller bandwidthω_(c)on the control system are analyzed,and the key parameters of ILADRC are optimally tuned online using improved gray wolf optimizer-radial basis function(IGWO-RBF)neural network.A simulationmodel is developed using MATLAB to simulate,analyze,and compare the method introduced in this paper.Simulations are performed with the traditional control strategy for comparison,and the results demonstrate that the proposed control method offers superior anti-interference performance.It effectively addresses power and frequency oscillation issues and enhances the stability of the VSG during grid-connected operation.

Unified Water Gravity Wave Theory and Improved Linear Wave

Based on Least Square Method, this paper presents variational principle for handling various water gravity wave theories and the unified water gravity wave theory was given. By using this variational principle of unified water wave theory, two kinds of improved linear waves were derived. The first one uses the same boundary conditions which were applied to derive 5-order Stokes wave. The second one uses the accurate boundary conditions (Eqs. 11 and 12). The two improved linear waves were compared with the existing linear wave.

Experimental Study on Calculation of Hydro-Geological Parameters for Unsteady Flow

After the linear analytical method of unsteady flow theory is further improved,an innovative and faster algorithm is introduced.The water storage in a confined aquifer is derived from the water transmissivity coefficient and the water-pressure conductivity coefficient.The water transmissivity coefficient is approximated by a Taylorseries expansion of drawdown,and the water-pressure conductivity coefficient is obtained by the average drawdown.In this algorithm,the distance of the observation points from the pumping well must be short.When the distance is as short as the radius of the main pumping well,the data of the drawdown difference between the sidewall and the center of pumping well are difficult to measure,but the same results can be achieved based on the assumption that the drawdown difference approximates to the drawdown of the observation wells at a radial distance from the pumping well according to the algorithm.Without the help of charts,this algorithm is more concise and efficient,which has been verified by the test of water pumping project in Tianjin Binhai International Airport.

Fast speedometer identification in dynamic scene based on phase correlation

Speedometer identification has been researched for many years.The common approaches to that problem are usually based on image subtraction,which does not adapt to image offsets caused by camera vibration.To cope with the rapidity,robust and accurate requirements of this kind of work in dynamic scene,a fast speedometer identification algorithm is proposed,it utilizes phase correlation method based on regional entire template translation to estimate the offset between images.In order to effectively reduce unnecessary computation and false detection rate,an improved linear Hough transform method with two optimization strategies is presented for pointer line detection.Based on VC＋＋ 6.0 software platform with OpenCV library,the algorithm performance under experiments has shown that it celerity and precision.

Web Voice Browser Based on an ISLPC Text-to-Speech Algorithm

A kind of Web voice browser based on improved synchronous linear predictive coding （ISLPC） and Text-toSpeech （TTS） algorithm and Internet application was proposed. The paper analyzes the features of TTS system with ISLPC speech synthesis and discusses the design and implementation of ISLPC TTS-based Web voice browser. The browser integrates Web technology, Chinese information processing, artificial intelligence and the key technology of Chinese ISLPC speech synthesis. It＇s a visual and audible web browser that can improve information precision for network users. The evaluation results show that ISLPC-based TTS model has a better performance than other browsers in voice quality and capability of identifying Chinese characters.

Fuzzy and IRLNC-based routing approach to improve data storage and system reliability in IoT

Internet of Things(IoT)based sensor network is largely utilized in various field for transmitting huge amount of data due to their ease and cheaper installation.While performing this entire process,there is a high possibility for data corruption in the mid of transmission.On the other hand,the network performance is also affected due to various attacks.To address these issues,an efficient algorithm that jointly offers improved data storage and reliable routing is proposed.Initially,after the deployment of sensor nodes,the election of the storage node is achieved based on a fuzzy expert system.Improved Random Linear Network Coding(IRLNC)is used to create an encoded packet.This encoded packet from the source and neighboring nodes is transmitted to the storage node.Finally,to transmit the encoded packet from the storage node to the destination shortest path is found using the Destination Sequenced Distance Vector(DSDV)algorithm.Experimental analysis of the proposed work is carried out by evaluating some of the statistical metrics.Average residual energy,packet delivery ratio,compression ratio and storage time achieved for the proposed work are 8.8%,0.92%,0.82%,and 69 s.Based on this analysis,it is revealed that better data storage system and system reliability is attained using this proposed work.

Microdamage study of granite under thermomechanical coupling based on the particle flow code

The thermomechanical coupling of rocks refers to the interaction between the mechanical and thermodynamic behaviors of rocks induced by temperature changes.The study of this coupling interaction is essential for understanding the mechanical and thermodynamic properties of the surrounding rocks in underground engineering.In this study,an improved temperature-dependent linear parallel bond model is introduced under the framework of a particle flow simulation.A series of numerical thermomechanical coupling tests are then conducted to calibrate the micro-parameters of the proposed model by considering the mechanical behavior of the rock under different thermomechanical loadings.Good agreement between the numerical results and experimental data are obtained,particularly in terms of the compression,tension,and elastic responses of granite.With this improved model,the thermodynamic response and underlying cracking behavior of a deep-buried tunnel under different thermal loading conditions are investigated and discussed in detail.

An improved algorithm for noise-robust sparse linear prediction of speech

The performance of linear prediction analysis of speech deteriorates rapidly under noisy environments. To tackle this issue, an improved noise-robust sparse linear prediction algorithm is proposed. First, the linear prediction residual of speech is modeled as Student-t distribution, and the additive noise is incorporated explicitly to increase the robustness, thus a probabilistic model for sparse linear prediction of speech is built, Furthermore, variational Bayesian inference is utilized to approximate the intractable posterior distributions of the model parameters, and then the optimal linear prediction parameters are estimated robustly. The experimental results demonstrate the advantage of the developed algorithm in terms of several different metrics compared with the traditional algorithm and the l1 norm minimization based sparse linear prediction algorithm proposed in recent years. Finally it draws to a conclusion that the proposed algorithm is more robust to noise and is able to increase the speech quality in applications.

Improved identification of glycerophospholipids using a linear ion trap mass spectrometer(LTQ) with Pulsed Q Collision Induced Dissociation(PQD)

Phospholipids are the major building blocks of the biological membranes. Additionally, phospholipids modulate membrane trafficking and metabolites derived from their