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.

Quantum Codes Do Not Increase Fidelity against Isotropic Errors

In this article, we study the ability of error-correcting quantum codes to increase the fidelity of quantum states throughout a quantum computation. We analyze arbitrary quantum codes that encode all qubits involved in the computation, and we study the evolution of n-qubit fidelity from the end of one application of the correcting circuit to the end of the next application. We assume that the correcting circuit does not introduce new errors, that it does not increase the execution time (i.e. its application takes zero seconds) and that quantum errors are isotropic. We show that the quantum code increases the fidelity of the states perturbed by quantum errors but that this improvement is not enough to justify the use of quantum codes. Namely, we prove that, taking into account that the time interval between the application of the two corrections is multiplied (at least) by the number of qubits n (due to the coding), the best option is not to use quantum codes, since the fidelity of the uncoded state over a time interval n times smaller is greater than that of the state resulting from the quantum code correction.

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.

Performance of entanglement-assisted quantum codes with noisy ebits over asymmetric and memory channels

Entanglement-assisted quantum error correction codes(EAQECCs)play an important role in quantum communications with noise.Such a scheme can use arbitrary classical linear code to transmit qubits over noisy quantum channels by consuming some ebits between the sender(Alice)and the receiver(Bob).It is usually assumed that the preshared ebits of Bob are error free.However,noise on these ebits is unavoidable in many cases.In this work,we evaluate the performance of EAQECCs with noisy ebits over asymmetric quantum channels and quantum channels with memory by computing the exact entanglement fidelity of several EAQECCs.We consider asymmetric errors in both qubits and ebits and show that the performance of EAQECCs in entanglement fidelity gets improved for qubits and ebits over asymmetric channels.In quantum memory channels,we compute the entanglement fidelity of several EAQECCs over Markovian quantum memory channels and show that the performance of EAQECCs is lowered down by the channel memory.Furthermore,we show that the performance of EAQECCs is diverse when the error probabilities of qubits and ebits are different.In both asymmetric and memory quantum channels,we show that the performance of EAQECCs is improved largely when the error probability of ebits is reasonably smaller than that of qubits.

Multiple bit upsets mitigation in memory by using improved hamming codes and parity codes

This paper combines improved Hamming codes and parity codes to assure the reliability of memory in presence of multiple bit upsets with low cost overhead.The redundancy bits of improved Hamming codes will be appended at the end of data bits,which eliminates the overhead of interspersing the redundancy bits at the encoder and decoder.The reliability of memory is further enhanced by the layout architecture of redundancy bits and data bits.The proposed scheme has been implemented in Verilog and synthesized using the Synopsys tools.The results reveal that the proposed method has about 19% less area penalties and 13% less power consumption comparing with the current two-dimensional error codes,and its latency of encoder and decoder is 63% less than that of Hamming codes.

Frame loss error concealment for SVC

Scalable video coding (SVC), as the Scalable Extension of H.264/AVC, is an ongoing international video coding standard designed for network adaptive or device adaptive applications and also offers high coding efficiency. However, packet losses often occur over unreliable networks even for base layer of SVC and have severe impact on the playback quality of compressed video. Until now, no literature has discussed error concealment support for standard SVC bit-stream. In this paper, we provide robust and effective error concealment techniques for SVC with spatial scalability. Experimental results showed that the proposed methods provide substantial improvement, both subjectively and objectively, without a significant complexity overhead.

Quaternion Integers Based Higher Length Cyclic Codes and Their Decoding Algorithm

The decoding algorithm for the correction of errors of arbitrary Mannheim weight has discussed for Lattice constellations and codes from quadratic number fields.Following these lines,the decoding algorithms for the correction of errors of n=p−12 length cyclic codes(C)over quaternion integers of Quaternion Mannheim(QM)weight one up to two coordinates have considered.In continuation,the case of cyclic codes of lengths n=p−12 and 2n−1=p−2 has studied to improve the error correction efficiency.In this study,we present the decoding of cyclic codes of length n=ϕ(p)=p−1 and length 2n−1=2ϕ(p)−1=2p−3(where p is prime integer andϕis Euler phi function)over Hamilton Quaternion integers of Quaternion Mannheim weight for the correction of errors.Furthermore,the error correction capability and code rate tradeoff of these codes are also discussed.Thus,an increase in the length of the cyclic code is achieved along with its better code rate and an adequate error correction capability.

Error code analysis and selection principle of M-ary modulation in network-based control systems

Error codes induced by M-ary modulation and modulation selection in network-based control systems are studied.It is the first time the issue of error codes induced by M-ary modulation is addressed in control field.In network-based control systems,error codes induced by noisy channel can significantly decrease the quality of control.To solve this problem,the network-based control system with delay and noisy channel is firstly modeled as an asynchronous dynamic system(ADS).Secondly,conditions of packet with error codes(PEC)loss rate by using M-ary modulation are obtained based on dynamic output feedback scheme.Thirdly,more importantly,the selection principle of M-ary modulation is proposed according to the measured signal-to-noise ratio(SNR)and conditions of PEC loss rate.Finally,system stability is analyzed and controller is designed through Lyapunov function and linear matrix inequality(LMI)scheme,and numerical simulations are made to demonstrate the effectiveness of the proposed scheme.

High Speed Versatile Reed-Solomon Decoder for Correcting Errors and Erasures

A new Chien search method for shortened Reed-Solomon （RS） code is proposed, based on this, a versatile RS decoder for correcting both errors and erasures is designed. Compared with the traditional RS decoder, the weighted coefficient of the Chien search method is calculated sequentially through the three pipelined stages of the decoder. And therefore, the computation of the errata locator polynomial and errata evaluator polynomial needs to be modified. The versatile RS decoder with minimum distance 21 has been synthesized in the Xilinx Virtex-Ⅱ series field programmable gate array （FPGA） xe2v1000-5 and is used by coneatenated coding system for satellite communication. Results show that the maximum data processing rate can be up to 1.3 Gbit/s.

Error Resilient Video Communication Based on Picture Level Adaptive Frame / Field Coding

Packet loss protection method based on picture level adaptive frame /field coding (PAFF)was presented. Firstly,the end-to-end rate-distortion analysis for PAFF on the current frame was performed. Secondly,in order to evaluate the severity of error propagation in the following frames,the error propagation intensity and human visual quality sensitivity of different areas were taken into consideration. It was followed by the quantification of relative importance. Finally,the proper coding mode was chosen utilizing an unequal comparison procedure. The simulation results show that the proposed method can improve peak signal-to-noise ratio (PSNR) up to 0. 9 dB and 1. 6 dB comparing with the field only and the dispersed flexible macro-block ordering (FMO)only methods respectively.

The Influence of Carrier Phase Error on the Performances of Digital Image m-QAM Transmission System

The effect of carrier phase error in digital image transmission system is discussed. Code error rate and SNR with carrier phase error in Gauss white noise channel are calculated, and the transmission system is simulated on computer.

STRONG CODING THEOREM AND ASYMPTOTIC ERROR EXPONENT OF ARBITRARILY VARYING SOURCE

Csiszar's strong coding theorem for discrete memoryless scarce is generalized to arbitrarily varying source.We also determine the asymptotic error exponent for arbitrarily wrying source.

Content based error resilience coding using redundant coding, reference frame modification, and mode decision

Quality degradation occurs during transmission of video streaming over the error-prone network. By jointly using redundant slice, reference frame selection, and intra/inters mode decision, a content and end-to-end rate-distortion based error resilience method is proposed. Firstly, the intra/inter mode decision is implemented using macro-block(MB) refresh, and then redundant picture and reference frame selection are utilized together to realize the redundant coding. The estimated error propagation distortion and bit consumption of refresh MB are used for the mode and reference frame decision of refresh MB. Secondly, by analyzing the statistical property in the successive frames, the error propagation distortion and bit consumption are formulated as a function of temporal distance. Encoding parameters of the current frame is determined by the estimated error propagation distortion and bit consumption. Thirdly, by comparing the rate-distortion cost of different combinations, proper selection of error resilience method is performed before the encoding process of the current frame. Finally, the MB mode and bit distribution of the primary picture are analyzed for the derivation of the texture information. The motion information is subsequently incorporated for the calculation of video content complexity to implement the content based redundant coding. Experimental results demonstrate that the proposed algorithm achieves significant performance gains over the LA-RDO and HRP method when video is transmitted over error-prone channel.

Majority Voting Procedure Allowing Soft Decision Decoding of Linear Block Codes on Binary Channels

In this paper we present an efficient algorithm to decode linear block codes on binary channels. The main idea consists in using a vote procedure in order to elaborate artificial reliabilities of the binary received word and to present the obtained real vector r as inputs of a SIHO decoder (Soft In/Hard Out). The goal of the latter is to try to find the closest codeword to r in terms of the Euclidean distance. A comparison of the proposed algorithm over the AWGN channel with the Majority logic decoder, Berlekamp-Massey, Bit Flipping, Hartman-Rudolf algorithms and others show that it is more efficient in terms of performance. The complexity of the proposed decoder depends on the weight of the error to decode, on the code structure and also on the used SIHO decoder.

On the Computing of the Minimum Distance of Linear Block Codes by Heuristic Methods

The evaluation of the minimum distance of linear block codes remains an open problem in coding theory, and it is not easy to determine its true value by classical methods, for this reason the problem has been solved in the literature with heuristic techniques such as genetic algorithms and local search algorithms. In this paper we propose two approaches to attack the hardness of this problem. The first approach is based on genetic algorithms and it yield to good results comparing to another work based also on genetic algorithms. The second approach is based on a new randomized algorithm which we call 'Multiple Impulse Method (MIM)', where the principle is to search codewords locally around the all-zero codeword perturbed by a minimum level of noise, anticipating that the resultant nearest nonzero codewords will most likely contain the minimum Hamming-weight codeword whose Hamming weight is equal to the minimum distance of the linear code.

Adaptive Learning Video Streaming with QoE in Multi-Home Heterogeneous Networks

In recent years,real-time video streaming has grown in popularity.The growing popularity of the Internet of Things(IoT)and other wireless heterogeneous networks mandates that network resources be carefully apportioned among versatile users in order to achieve the best Quality of Experience(QoE)and performance objectives.Most researchers focused on Forward Error Correction(FEC)techniques when attempting to strike a balance between QoE and performance.However,as network capacity increases,the performance degrades,impacting the live visual experience.Recently,Deep Learning(DL)algorithms have been successfully integrated with FEC to stream videos across multiple heterogeneous networks.But these algorithms need to be changed to make the experience better without sacrificing packet loss and delay time.To address the previous challenge,this paper proposes a novel intelligent algorithm that streams video in multi-home heterogeneous networks based on network-centric characteristics.The proposed framework contains modules such as Intelligent Content Extraction Module(ICEM),Channel Status Monitor(CSM),and Adaptive FEC(AFEC).This framework adopts the Cognitive Learning-based Scheduling(CLS)Module,which works on the deep Reinforced Gated Recurrent Networks(RGRN)principle and embeds them along with the FEC to achieve better performances.The complete framework was developed using the Objective Modular Network Testbed in C++(OMNET++),Internet networking(INET),and Python 3.10,with Keras as the front end and Tensorflow 2.10 as the back end.With extensive experimentation,the proposed model outperforms the other existing intelligentmodels in terms of improving the QoE,minimizing the End-to-End Delay(EED),and maintaining the highest accuracy(98%)and a lower Root Mean Square Error(RMSE)value of 0.001.

Novel Double Modular Redundancy Based Fault-Tolerant FIR Filter for Image Denoising

In signal processing and communication systems,digital filters are widely employed.In some circumstances,the reliability of those systems is crucial,necessitating the use of fault tolerant filter implementations.Many strategies have been presented throughout the years to achieve fault tolerance by utilising the structure and properties of the filters.As technology advances,more complicated systems with several filters become possible.Some of the filters in those complicated systems frequently function in parallel,for example,by applying the same filter to various input signals.Recently,a simple strategy for achieving fault tolerance that takes advantage of the availability of parallel filters was given.Many fault-tolerant ways that take advantage of the filter’s structure and properties have been proposed throughout the years.The primary idea is to use structured authentication scan chains to study the internal states of finite impulse response(FIR)components in order to detect and recover the exact state of faulty modules through the state of non-faulty modules.Finally,a simple solution of Double modular redundancy(DMR)based fault tolerance was developed that takes advantage of the availability of parallel filters for image denoising.This approach is expanded in this short to display how parallel filters can be protected using error correction codes(ECCs)in which each filter is comparable to a bit in a standard ECC.“Advanced error recovery for parallel systems,”the suggested technique,can find and eliminate hidden defects in FIR modules,and also restore the system from multiple failures impacting two FIR modules.From the implementation,Xilinx ISE 14.7 was found to have given significant error reduction capability in the fault calculations and reduction in the area which reduces the cost of implementation.Faults were introduced in all the outputs of the functional filters and found that the fault in every output is corrected.

Turbo Code Simulation in W-CDMA System

Turbo code has drawn more and more attractions for high data rate transmission these years especially in W CDMA and CDMA2000 of the third generation mobile communications systems. In this paper, the simulation performance of turbo code under Rayleigh fading channel and additive white Gaussian channels are depicted. Comparison with the performance of convolutional code are made respect to different parameters, such as pilot length, interleaver size, frame length, mobile velocity and data rate, etc. Faithful results are drawn out.

Multiparty Quantum Secret Sharing Using Quantum Fourier Transform

A （n, n）-threshold scheme of multiparty quantum secret sharing of classical or quantum message is proposed based on the discrete quantum Fourier transform. In our proposed scheme, the secret message, which is encoded by using the forward quantum Fourier transform and decoded by using the reverse, is split and shared in such a way that it can be reconstructed among them only if all the participants work in concert. Fhrthermore, we also discuss how this protocol must be carefully designed for correcting errors and checking eavesdropping or a dishonest participant. Security analysis shows that our scheme is secure. Also, this scheme has an advantage that it is completely compatible with quantum computation and easier to realize in the distributed quantum secure computation.

Real-time video compression system design and hardware implementation based on multiple ADV212

In order to improve the transmission rate of the compression system,a real-time video lossy compression system based on multiple ADV212 is proposed and achieved. Considering the CMOS video format and the working principle of ADV212,a Custom-specific mode is used for various video formats firstly. The data can be cached through the FPGA internal RAM and SDRAM Ping-Pong operation. And the working efficiency is greatly promoted. Secondly,this method can realize direct code stream transmission or do it after storage. Through the error correcting coding,the correction ability of the flash memory is highly improved. Lastly,the compression and de-compression circuit boards are involved to specify the performance of the method. The results show that the compression system has a real-time and stable performance. And the compression ratio can be changed arbitrarily by configuring the program. The compression system can be realized and the real-time performance is good with large amount of data.