A Steady-State Errors Correction Method for Eliminating Measurement Errors

This paper proposes a steady-state errors correction(SSEC)method for eliminating measurement errors.This method is based on the detections of error signal E(s)and output C(s)which generate an expected output R(s).In comparison with the conventional solutions which are based on detecting the expected output R(s)and output C(s)to obtain error signal E(s),the measurement errors are eliminated even the error might be at a significant level.Moreover,it is possible that the individual debugging by regulating the coefficient K for every member of the multiple objectives achieves the optimization of the open loop gain.Therefore,this simple method can be applied to the weak coupling and multiple objectives system,which is usually controlled by complex controller.The principle of eliminating measurement errors is derived analytically,and the advantages comparing with the conventional solutions are depicted.Based on the SSEC method analysis,an application of this method for an active power filter(APF)is investigated and the effectiveness and viability of the scheme are demonstrated through the simulation and experimental verifications.

Application of the Analogue-Based Correction of Errors Method in ENSO Prediction

In this study, a method of analogue-based correction of errors(ACE) was introduced to improve El Ni?o-Southern Oscillation(ENSO) prediction produced by climate models. The ACE method is based on the hypothesis that the flow-dependent model prediction errors are to some degree similar under analogous historical climate states, and so the historical errors can be used to effectively reduce such flow-dependent errors. With this method, the unknown errors in current ENSO predictions can be empirically estimated by using the known prediction errors which are diagnosed by the same model based on historical analogue states. The authors first propose the basic idea for applying the ACE method to ENSO prediction and then establish an analogue-dynamical ENSO prediction system based on an operational climate prediction model. The authors present some experimental results which clearly show the possibility of correcting the flow-dependent errors in ENSO prediction, and thus the potential of applying the ACE method to operational ENSO prediction based on climate models.

Analogue correction method of errors and its application to numerical weather prediction

In this paper, an analogue correction method of errors （ACE） based on a complicated atmospheric model is further developed and applied to numerical weather prediction （NWP）. The analysis shows that the ACE can effectively reduce model errors by combining the statistical analogue method with the dynamical model together in order that the information of plenty of historical data is utilized in the current complicated NWP model, Furthermore, in the ACE, the differences of the similarities between different historical analogues and the current initial state are considered as the weights for estimating model errors. The results of daily, decad and monthly prediction experiments on a complicated T63 atmospheric model show that the performance of the ACE by correcting model errors based on the estimation of the errors of 4 historical analogue predictions is not only better than that of the scheme of only introducing the correction of the errors of every single analogue prediction, but is also better than that of the T63 model.

An Empirical Study of Using Imitation-Based Error Correction to Reduce Repeated Errors in English Writing of Rural Junior High School Students

Junior high school students in rural areas constitute a particular group of English learners, for whom English writing is not only important, but also difficult. In order to find out an effective means to help them enhance English writing proficiency. To this end, after carefully analyzing the writing characteristics of this group of English learners, one intact class in Grade 8 of No. 14 junior middle school in Wuwei was given an experimental treatment which required them to imitate the correct examples of expressions provided by their teacher where they used to make errors. Results revealed that students in experimental class outperform their peers in control class significantly.

Single Photon Detection Technology in Underwater Wireless Optical Communication:Modulation Modes and Error Correction Coding Analysis

This study explores the application of single photon detection(SPD)technology in underwater wireless optical communication(UWOC)and analyzes the influence of different modulation modes and error correction coding types on communication performance.The study investigates the impact of on-off keying(OOK)and 2-pulse-position modulation(2-PPM)on the bit error rate(BER)in single-channel intensity and polarization multiplexing.Furthermore,it compares the error correction performance of low-density parity check(LDPC)and Reed-Solomon(RS)codes across different error correction coding types.The effects of unscattered photon ratio and depolarization ratio on BER are also verified.Finally,a UWOC system based on SPD is constructed,achieving 14.58 Mbps with polarization OOK multiplexing modulation and 4.37 Mbps with polarization 2-PPM multiplexing modulation using LDPC code error correction.

Analysis and correction of the machining errors of small plastic helical gears by ball-end milling

Many small-size precise plastic helical involutes gears are used in electrical appliances to transmit rotary movements con- tinuously and smoothly. Ball-end milling is an effective method for trial manufacture or small batch production of this type of gear, but the precision of the gear is usually low. In this research, the main sources of the errors of the gear, machining errors of the tooth profile and trace of the gear obtained were analyzed. The correction amounts for these errors are then determined by using a CNC gear tester. They are used to generate a new 3D-CAD model for gear machining with better nrecision.

Calculation and correction of magnetic object positioning error caused by magnetic field gradient tensor measurement

Magnetic field gradient tensor measurement is an important technique to obtain position information of magnetic objects. When using magnetic field sensors to measure magnetic field gradient as the coefficients of tensor, field differentiation is generally approximated by field difference. As a result, magnetic objects positioning by magnetic field gradient tensor measurement always involves an inherent error caused by sensor sizes, leading to a reduction in detectable distance and detectable angle. In this paper, the inherent positioning error caused by magnetic field gradient tensor measurement is calculated and corrected by iterations based on the systematic position error distribution patterns. The results show that, the detectable distance range and the angle range of an ac magnetic object（2.44 Am^2@1 kHz） can be increased from（0.45 m, 0.75 m）,（0？, 25？） to（0.30 m, 0.80 m）,（0？,80？）, respectively.

Quantum computation and error correction based on continuous variable cluster states

Measurement-based quantum computation with continuous variables,which realizes computation by performing measurement and feedforward of measurement results on a large scale Gaussian cluster state,provides a feasible way to implement quantum computation.Quantum error correction is an essential procedure to protect quantum information in quantum computation and quantum communication.In this review,we briefly introduce the progress of measurement-based quantum computation and quantum error correction with continuous variables based on Gaussian cluster states.We also discuss the challenges in the fault-tolerant measurement-based quantum computation with continuous variables.

3D Trajectory Planning of Positioning Error Correction Based on PSO-A* Algorithm

Aiming at the yaw problem caused by inertial navigation system errors accumulation during the navigation of an intelligent aircraft,a three-dimensional trajectory planning method based on the particle swarm optimization-A star(PSO-A*)algorithm is designed.Firstly,an environment model for aircraft error correction is established,and the trajectory is discretized to calculate the positioning error.Next,the positioning error is corrected at many preset trajectory points.The shortest trajectory and the fewest correction times are regarded as optimization goals to improve the heuristic function of A star(A*)algorithm.Finally,the index weights are continuously optimized by the particle swarm optimization algorithm.The optimal trajectory is found by the A*algorithm under the current evaluation index,so the ideal trajectory is planned.The experimental results show that the PSO-A*algorithm can quickly search for ideal trajectories in different environment models,indicating that the algorithm has certain feasibility and adaptability,and verifies the rationality of the proposed trajectory planning model.The PSO-A*algorithm has better convergence accuracy than the A*algorithm,and the search efficiency is significantly better than the grid search A star(GS-A*)algorithm.The PSO-A*algorithm proposed in this paper has certain engineering application value.The researchers will study the real-time and systematic nature of the algorithm.

Near field 3-D imaging approach for joint high-resolution imaging and phase error correction

This paper combines compressed sensing (CS) imaging theory and range migration algorithm (RMA), and then proposes a near-field three-dimensional (3-D) imaging approach for joint high-resolution imaging and phase error correction. Firstly, a sparse measurement matrix construction method based on a logistic sequence is proposed, which conducts nonlinear transformation for the determined logistic sequence, making it obey uniform distribution, then conducts sign function mapping, and generates the pseudorandom sequence with Bernoulli distribution, thus leading to good signal recovery under down-sampling and easy availability for engineering realization. Secondly, in combination with the RMA imaging approach, the dictionary with all scene information and phase error correction is constructed for CS signal recovery and error correction. Finally, the non-quadratic solution model jointing imaging and phase error correction based on regularization is built, and it is solved by two steps - the separable surrogate functionals (SSF) iterative shrinkage algorithm is adopted to realize target scattering estimate; the iteration mode is adopted for the correction of the dictionary model, so as to achieve the goal of error correction and highly-focused imaging. The proposed approach proves to be effective through numerical simulation and real measurement in anechoic chamber. The results show that, the proposed approach can realize high-resolution imaging in the case of less data; the designed measurement matrix has better non-coherence and easy availability for engineering realization. The proposed approach can effectively correct the phase error, and achieve highly-focused target image. © 2017 Beijing Institute of Aerospace Information.

Tooth surface error correction of hypoid gears machined by duplex helical method

In this work,synchronous cutting of concave and convex surfaces was achieved using the duplex helical method for the hypoid gear,and the problem of tooth surface error correction was studied.First,the mathematical model of the hypoid gears machined by the duplex helical method was established.Second,the coordinates of discrete points on the tooth surface were obtained by measurement center,and the normal errors of the discrete points were calculated.Third,a tooth surface error correction model is established,and the tooth surface error was corrected using the Levenberg-Marquard algorithm with trust region strategy and least square method.Finally,grinding experiments were carried out on the machining parameters obtained by Levenberg-Marquard algorithm with trust region strategy,which had a better effect on tooth surface error correction than the least square method.After the tooth surface error is corrected,the maximum absolute error is reduced from 30.9μm before correction to 6.8μm,the root mean square of the concave error is reduced from 15.1 to 2.1μm,the root mean square of the convex error is reduced from 10.8 to 1.8μm,and the sum of squared errors of the concave and convex surfaces was reduced from 15471 to 358μm^(2).It is verified that the Levenberg-Marquard algorithm with trust region strategy has a good accuracy for the tooth surface error correction of hypoid gear machined by duplex helical method.

Parameter-independent error correction for potential measurements by reference electrode in lithium-ion batteries

The safety monitoring of lithium-ion batteries(LIBs) is of great significance for realizing all-climate and full-lifespan battery management. In-situ measurement of anode potential with implanted reference electrodes(REs) has proven to be effective to monitor and avoid the occurrence of severe side reactions like Li plating to ensure the safe and fast charging. However, the intrinsic measurement errors caused by local blocking effects, which also can be referred to as potential artefacts, are seldom taken into consideration in existing studies, yet they highly dominate the correctness of conclusions inferred from REs. In this study, aiming at exploring the physical origin of the measurement errors and ensure reliable potential monitoring, electrochemical and post-mortem tests are conducted using commercial pouch cells with implanted REs. Corresponding electrochemical model which describes the blocking effects, is established to validate the abnormal absence of lithium plating that predicted by measured anode potentials under various charging rates. Theoretical derivation is further presented to explain the error sources, which can be attributed to increased local liquid potential of the RE position. Most importantly, with the guidance of error analysis, a novel parameter-independent error correction method for RE measurements is proposed for the first time, which is proven to be adequate to estimate the real anode potentials and deduce the critical C-rate of Li plating with extra safety margin. After error correction, the resulting critical C-rates are all within the range of 0.55 ± 0.03 C, which is close to the C-rate of 0.6–0.7 C obtained from experiments. In addition, this error correction method can be performed conveniently with only some simple RE measurements of polarization voltages, totally independent of battery electrochemical and geometric parameters. This study provides highly practical error correction method for RE measurements in real LIBs, substantially facilitating the fast diagnosis and safety evaluation of Li plating during charging of LIBs.

Planning of circlelocus for multi-path/multi-layer welding robot with automatical error-correction

In this paper, a planning algorithm for multi path/multi layer circular locus is poposed. The algorithm is applied to weld the nipples on the header of boiler. Multi path/multi layer circular locus is planned according to three teaching points, which is lapped head on end to satisfy the requirement of technology. For the nipples wherever they are arranged radially or axially, even if there are errors caused by positioning and thermal deformations, providing that nipple's position and orientation relative to the teaching one can be measured, the multi path/multi layer circular locus can be planned without teaching any more. The algorithm has been applied in welding robot for manufacturing power station' boiler.

Determination of quantum toric error correction code threshold using convolutional neural network decoders

Quantum error correction technology is an important solution to solve the noise interference generated during the operation of quantum computers.In order to find the best syndrome of the stabilizer code in quantum error correction,we need to find a fast and close to the optimal threshold decoder.In this work,we build a convolutional neural network(CNN)decoder to correct errors in the toric code based on the system research of machine learning.We analyze and optimize various conditions that affect CNN,and use the RestNet network architecture to reduce the running time.It is shortened by 30%-40%,and we finally design an optimized algorithm for CNN decoder.In this way,the threshold accuracy of the neural network decoder is made to reach 10.8%,which is closer to the optimal threshold of about 11%.The previous threshold of 8.9%-10.3%has been slightly improved,and there is no need to verify the basic noise.

Novel multipath routing protocol integrated with forward error correction in MANET

In order to improve the data transmission reliability of mobile ad hoc network, a routing scheme called integrated forward error correction multipath routing protocol was proposed, which integrates the techniques of packet fragmenting and forward error correction encoding into multipath routing. The scheme works as follows: adding a certain redundancy into the original packets; fragmenting the resulting packets into exclusive blocks of the same size; encoding with the forward error correction technique, and then sending them to the destination node. When the receiving end receives a certain amount of information blocks, the original information will be recovered even with partial loss. The performance of the scheme was evaluated using OPNET modeler. The experimental results show that with the method the average transmission delay is decreased by 20% and the transmission reliability is increased by 30%.

Research on the Relationship between Income and Consumption of the Urban Residents in Hunan Province on the Basis of Error Correction Model

By using error correction model, I conduct co-integration analysis on the research of the relationship between the per capita practical consumption and per capita practical disposable income of urban residents in Hunan Province from 1978 to 2009. The results show that there is a co-integration relationship between the per capita practical consumption and the practical per capita disposable income of urban residents, and based on these, the corresponding error correction model is established. Finally, corresponding countermeasures and suggestions are put forward as follows: broaden the income channel of urban residents; create goods consuming environment; perfect socialist security system.

A Comparison of Error Correction Models for Student’s Error Codes Based on Deep Learning

Automatically correcting students’code errors using deep learning is an effective way to reduce the burden of teachers and to enhance the effects of students’learning.However,code errors vary greatly,and the adaptability of fixing techniques may vary for different types of code errors.How to choose the appropriate methods to fix different types of errors is still an unsolved problem.To this end,this paper first classifies code errors by Java novice programmers based on Delphi analysis,and compares the effectiveness of different deep learning models(CuBERT,GraphCodeBERT and GGNN)fixing different types of errors.The results indicated that the 3 models differed significantly in their classification accuracy on different error codes,while the error correction model based on the Bert structure showed better code correction potential for beginners’codes.

Error Correction Strategy Use in the Second Language Classroom： A Study of Junior High School English Teachers in Ghana

Error correction, in recent times, is seen as one of the important teaching processes in L2 （second language） learning, because comprehensible inputs alone is insufficient for acquisition of language. However, few L2 teachers know much about error analysis and how to correct errors in the L2 classroom. Error correction is a very complicated and a thorny issue in L2 teaching and learning. L2 teachers, therefore, need to be armed with ways in which errors can be treated to ensure maximum effect yet with less harm to learners. Identifying learners＇ errors is very important in L2 learning, but how to correct them to give the desired effect is equally important and very challenging to L2 teachers. It is therefore crucial to initiate a study in Ghana to find out how errors are corrected in the Ghanaian English language classroom. This case study used complete observation and semi-structured interview as data collection strategies to identify error correction strategies/types English teachers use in the Ghanaian JHS （Junior High School） classroom and how error correction/treatment can be improved to facilitate English language teaching and learning. The findings of the study showed that explicit error correction technique was the most commonly used followed by recast, elicitation, metalinguistic clues, clarification request, repetition, and cues. It was also found that the causes of the disparity in the use of the various error correction types were inadequate teacher preparation, incompetence in English language, limited knowledge in error correction, caliber of students, and insufficient teaching time. This study identified that the situation can be improved through effective teacher training, in-service training, learner involvement, and effective planning.

Research on Error Analysis and Correction Technique of Atmospheric Refraction for InSAR Measurement with Distributed Satellites

SAR interferometry with distributed satellites is a technique based on the exploitation of the interference pattern of two SAR images acquired synchronously. The interferogram contains geometric, atmospheric, topographic and land defomation. This paper focuses on atmospheric effects on SAR interferometry, which shows theoretically that the relationship among ionosphere TEC and troposphere parameters such as temperature, relative humitdity and pressure with respect to slant rang changes. An atmospheric correction method is given in the end.

Error Correction Circuit for Single-Event Hardening of Delay Locked Loops

In scaled CMOS processes, the single-event effects generate missing output pulses in Delay-Locked Loop (DLL). Due to its effective sequence detection of the missing pulses in the proposed Error Correction Circuit (ECC) and its portability to be applied to any DLL type, the ECC mitigates the impact of single-event effects and completes its operation with less design complexity without any concern about losing the information. The ECC has been implemented in 180 nm CMOS process and measured the accuracy of mitigation on simulations at LETs up to 100 MeV-cm2/mg. The robustness and portability of the mitigation technique are validated through the results obtained by implementing proposed ECC in XilinxArtix 7 FPGA.