最新刊期
卷 49 ， 期 11 ， 2021
- 摘要：Software ecology is one of the most critical factors restricting the development of RISC-V instruction set architecture. Allowing the RISC-V processor to directly run the ARM Thumb binary code can solve its software ecological problem in the embedded field to a certain extent. Based on the binary translation, this article realizes support for the ARM Thumb program and achieves comparable performance on the RISC-V processor with the lower area and power consumption overhead by using hardware to optimize ARM Thumb flag bits, branch instructions, and conditional execution. For the Embench benchmark suite, the average performance of the processor running ARM Thumb programs can reach 75.5% of directly running RISC-V programs. Compared with using only binary translation to support ARM Thumb, hardware optimization performance is improved by 3.1 times and hardware overhead is reduced by 7.8%.关键词：RISC-V;ARM Thumb;architecture;multiple-ISA;microprocessor;binary translation11|20|2更新时间：2025-12-08
- 摘要：Bloom filters are often used in the LSM(Log-Structured-Merge) tree to reduce unnecessary disk I/O. However, users cannot refine the granularity of Bloom filters infinitely, because in some workflows with huge data volume and small data items, these metadata require a lot of storage space. Secondly, in some memory-constrained environments, the cache cannot accommodate more filter data, resulting in frequent data exchange between memory and disk. In view of the above problems, we propose a heterogeneous Bloom filter scheme in LSM tree. The hotness prediction model is maintained at each layer of the LSM tree, and the newly generated disk components are distributed with different granularity according to the predicted hotness. And a specific cache management scheme is used to maintain the filter data in memory cache and deal with changes in workflow hotness. It is experimentally proven that the proposed scheme improves read throughput by 22%~53% over LevelDB with the original LSM tree structure while maintaining the same storage occupation and memory consumption.关键词：log-structured-merge-tree;key-value store;read performance;Bloom filter;storage management;hotness prediction6|16|0更新时间：2025-12-08
- 摘要：Community search aims to find personalized communities highly related to the given query nodes. Existing community search methods are applicable to simple networks, and always assume either a single query node is given or multiple query nodes are from the same community, which limits the flexibility of the algorithm. An attributed network oriented multi-community search method, which is designed via random walk path similarity enhancement of query nodes, is proposed to effectively locate multiple local communities that query node belongs. Attribute and high-order structure information in the network are effectively fused, and the importance score vector of each query node is calculated based on random walk with restart. The similarity between random walk paths of query nodes is calculated and the similarity enhancement strategy is designed to enhance the association of similar path walkers so as to locate multiple community structures of different query nodes. Based on the combination of structure and attribute, the parallel conductance is used to accurately find the community. The experiments on both real-world datasets and synthetic datasets verify the effectiveness and efficiency of the proposed method.关键词：attributed networks;high-order structure;similarity-enhanced random walk;parallel conductance;community search2|20|1更新时间：2025-12-08
- 摘要：In recent years, the multi-objective evolutionary methods have been widely used for solving overlapping community detection problem and have achieved good community division performance. To design appropriate individual encoding and evolution strategies is important to improve the performance of multi-objective overlapping community detection evolutionary algorithm. To this end, a dual representation method is designed to encode the non-overlapping community structures and overlapping nodes respectively, which can effectively obtain the overlapping community structures. On the basis of the dual representation, this paper proposes a dual representation-based multi-objective evolutionary algorithm for overlapping community detection (DRMOEA). In DRMOEA, an initialization strategy based on community boundary nodes is suggested to obtain good initial individuals，with the aim to improve the detection performance of the algorithm. In addition, for the overlapping part of the dual-representation, this paper proposes a crossover strategy according to the boundary nodes of elite individuals, which uses community boundary information to guide the evolution of the population towards a better direction. Finally, the experimental results on nine real-world networks show that the proposed DRMOEA is better than five representative baseline overlapping community detection algorithms.关键词：complex network;overlapping community detection;dual representation;multi-objective optimization8|26|1更新时间：2025-12-08
- 摘要：Target recognition is gradually becoming an important technology to provide accurate target category information in the field of automation, and most current target recognition methods are based on machine learning frameworks. Generally, the input data of the machine learning framework is raw image data, but in practical applications, the way that the detector obtains the raw image data and uses it as the input of the deep learning framework to achieve target recognition is low efficient, contains a lot of redundant information, which reduces the recognition efficiency. In this paper, by combining machine learning and compressive sensing technology, a new target recognition method named as target recognition technology based on a new joint sensing matrix for compressed learning (TRNPCL) is proposed. Through the proposed method, the detector can quickly generate multi-dimensional compressed data of the target image, and the compressed data can be directly used as the input data of the deep learning target recognition framework without further decompression steps, which not only greatly reduces the amount of data input to the machine learning framework, but also maintains a higher recognition accuracy compared with the single-space domain data compression learning method under the same compression ratio. In the future, this method is expected to become a more effective and flexible target recognition method, and especially suitable for fingerprint recognition, face recognition and other application fields.关键词：compressed sensing;deep learning;target recognition;compression coding;image processing5|20|1更新时间：2025-12-08
- 摘要：For the performance degradation problem of target azimuth estimation method based on frequency domain compressed sensing, the complex domain signal was obtained via complex analytical transformation of the array pickup data, and the complex domain sensing matrix and measured value were constructed after the time delay compensating, correlation and accumulation processing of each channel data. Then, the spatial spectrum was synthesized through the compressed sensing method in complex domain, and the target azimuth estimation value was obtained. The processing results of numerical simulation and measured data show that, for the same detection probability and compared with frequency domain compressed sensing, the demand of input signal to noise ratio of this method was reduced by nearly 10lgMdB (M is the channel number of array), and the ability of weak target detection was enhanced.关键词：array signal processing;target azimuth estimation;complex domain compressed sensing;complex domain sensing matrix3|18|2更新时间：2025-12-08
- 摘要：The LEO mega-constellation network with inter-satellite links faces serious network congestion when multi-commodity traffics return to a limited geographical area from all over the world, which can be alleviated by centralized traffic planning. However, the computing time cost of large-scale network planning cannot meet the dynamic requirements of LEO constellation. Therefore, this paper proposes a low complexity Multi-Commodity Flow Segment Routing (MCFSR) algorithm, which divides the constellation-ground network into two zones according to different link payload, and balances between accuracy and complexity of the planning algorithm in each zone, so as to reduce the overall time complexity. Meanwhile, for the planning algorithm, this paper proposes an Improved Fully Polynomial Time Approximation (IFPTA) algorithm with adjustable precision and complexity for routing programming in each zone, which improves the planning accuracy without changing the computational complexity. Simulation results show that the total throughput of multi traffic backhaul programmed by proposed MCFSR algorithm approaches the optimal, with the time complexity far less than other similar algorithms.关键词：LEO mega-constellation;multi-traffic backhaul;load balancing;multi-commodity flow;segment routing;time complexity3|23|0更新时间：2025-12-08
- 摘要：Facing the challenges of the transmission resource schedule of dense space networks, we combine the mathematical models and machine learning methods, and propose a graph learning based approach for the scheduling of transmission resources in dense space networks. In the proposed method, transmission resource scheduling problem is decomposed based on the knowledge of the problem structure brought by graph theory. On this basis, mathematical model and reinforcement learning alternately complete the whole solution process. Simulation results show that, compared with the traditional mathematical model-based methods, the proposed method improves the scheduling profits by 25.1%, and its training results have better generality.关键词：dense space network;resource scheduling;machine learning;deep reinforcement learning;graph theory3|16|0更新时间：2025-12-08
- 摘要：In order to solve the problem that the user grouping of non‑orthogonal multiple access (NOMA) in the mm‑wave massive MIMO system is limited by the beam width of the base station, a beamforming scheme which can generate beams pointing in multiple directions is proposed. Based on the multi‑beam beamforming scheme, a mathematical model of user resource allocation in multi‑cell and multi‑user scenario is established. In order to reduce the complexity of computation, a two‑stage resource allocation algorithm is adopted. In the first stage, under the given power allocation conditions, the model is transformed into the coalition generation in the coalition game theory, and an algorithm for iteratively determining user grouping and antenna unit allocation is proposed; in the second stage, an algorithm of user power allocation is proposed by transforming the non‑convex mathematical optimization problem into a DC programming problem. The simulation results show that the proposed multi‑beam beamforming scheme can effectively generate beams pointing to multiple directions, and the proposed resource allocation algorithm can effectively improve the performance of the system.关键词：non‑orthogonal multiple access(NOMA);beamforming;massive MIMO3|16|1更新时间：2025-12-08
- 摘要：As an important code domain non orthogonal multiple access technology, sparse code division multiple access (SCMA) can meet the requirements of 5G communication for massive machine access. However, the message passing algorithm (MPA) adopted by the receiver has the problems of slow convergence speed and high computational complexity. This paper proposes an edge serial message passing algorithm based on subgraph (SE-MPA). The original factor graph is divided into several different subgraphs. Based on the subgraph, the message update sequence is optimized, and the edge serial update sequence set is adopted. The updated user node messages are used to update the connected resource nodes immediately. Simulation results show that the algorithm can effectively speed up the message convergence and reduce the computational complexity in the case of a small amount of BER performance loss.关键词：sparse code multiple access;message passing algorithm;subgraph;edge serial;convergence rate;computational complexity2|20|0更新时间：2025-12-08
- 摘要：With the rapid growth of video data, the demand for large-scale video processing tasks increases dramatically. How to process video data in time to obtain effective information and provide users with video analysis services quickly is an important issue to be solved. Aiming at this problem, a new deployment method of Edge Functions Modularized and Reorganized (EFMR) for large-scale video processing is proposed. This method sinks video processing services to the edge of the network. Using network function virtualization, video service requests sent to the edge server are divided fine-grainedly based on their inherent process correlation, and resources are matched and redeployed on demand based on the division results. In this way, we can smoothly expand the edge video service processing capabilities at a small cost. Experimental results show that EFMR method not only greatly reduces the edge server’s access and response delay, reduces the inference time, but also saves a lot of computing resources of edge servers and speeds up the deployment of video processing services.关键词：mobile edge computing;network function virtualization;modular;reorganized;fine-grained2|16|1更新时间：2025-12-08
- 摘要：In order to solve the problems of noise amplification, insufficient detail and color restoration in the process of low‑light image enhancement, this paper proposes a method of low‑light image enhancement based on attention residual dense‑generative adversarial networks (ARD‑GAN). Firstly, the method generates a global exposure attention map in the global illumination estimation module (GIEM) to guide the subsequent modules to enhance the illumination better; secondly, it adopts the convolution and residual module (CRM) and the channel attention residual dense module (CARDM) to extract shallow features and deep features respectively, and fuses different features of levels to obtain better detailed information; furthermore, based on the CARDM, the dense connection and batch normalization are combined to suppress noise. Finally, the improved loss function restores the enhanced image color better. Comprehensive experiments are conducted, which show that ARD‑GAN can significantly outperform mainstream algorithms in subjective vision and objective evaluation indicators.关键词：low‑light enhancement;image detail enhancement;noise reduction;color reproduction;attention mechanism;residual dense network11|21|8更新时间：2025-12-08
- 摘要：After carefully analyzing the characteristics of existing low light image enhancement (LLIE) algorithms, we proposed a hybrid LLIE (HLLIE) algorithm with two-stage hybrid strategy. Specifically, in the first stage, for a given low-light image, we chose the complementary LLIE algorithms, i.e., Fu and Ying, to enhance the low-light image, respectively. In the second stage, the two preliminary enhanced images were used as the inputs of the multi-channel shallow convolution neural network (MSCNN), and then the pre-trained MSCNN conducted optimal combination of the two preliminary enhanced images to achieve further enhancement regarding the image quality. The experimental results show that, compared with the state-of-the-art LLIE algorithms, the HLLIE algorithm has obvious advantages in terms of the objective image quality metrics on the low-light images, and the subjective evaluation also can confirm this.关键词：low-light image enhancement;two-stage hybrid strategy;initial enhanced image;multi-channel shallow convolution neural network;combination3|22|3更新时间：2025-12-08
- 摘要：Aiming at the problems of complex scenes and rich texture features of UAV landing landform image, a classification algorithm of UAV landing landform image based on wavelet transform and deep network is proposed. Using the fast compression capability of non-subsampled wavelet transform (NSWT), the first two layers of sub-image coefficients after wavelet transform are introduced into the convolutional neural network (CNN) to compress the amount of data. According to the characteristics of UAV landing landform image, a 15-layer convolutional neural network is designed using a lightweight convolution module. The correct classification of complex geomorphological scenes is realized by support vector machine (SVM). The experimental results show that the proposed algorithm has good feature expression ability and improves the classification accuracy of landing landform images.关键词：non-subsampled wavelet transform;convolutional neural network;support vector machine;image classification2|21|1更新时间：2025-12-08
- 摘要：To address the problems of poor robustness, lack of language modeling ability and inability to distinguish between homophones or near-tone characters effectively in the recognition of Chinese speech, an end-to-end Chinese speech recognition algorithm integrating language model is proposed. Firstly, an acoustic model from speech to Pinyin is established based on Deep Fully Convolutional Neural Network (DFCNN) and Connectionist Temporal Classification (CTC). Then the language model from Pinyin to Chinese character is constructed by using the encoder of Transformer. Finally, the speech frame decomposition model is designed to link the output of the acoustic model with the input of the language model, which overcomes the difficulty that the gradient of loss function cannot be passed from the language model to the acoustic model, and realizes the end-to-end training of the acoustic model and the language model. Real data sets are applied to verify the proposed method. Experimental results show that the introduction of language model reduces the word error rate (WER) of the algorithm by 21%, and the end-to-end integrating training algorithm plays a key role, which improves the performance by 43%. Compared with five up-to-date algorithms, our method achieves a 28% WER, lower than that of the best model among comparison methods—DeepSpeech2.关键词：speech recognition;CTC;language model;acoustic model;speech frame decomposition5|21|4更新时间：2025-12-08
- 摘要：As one of the most important methods in speaker verification, the identity-vector (i-vector) approach can obtain effective low-dimensional i-vector by learning the total variability space (TVS). However, when there is no sufficient development data, it will lead to a large error in the learned TVS model. Meanwhile, it is difficult to determine whether there is redundancy in the learned TVS due to the high preset dimension. To solve the above problems, the Bayesian principal component analysis (BPCA) is introduced into the learning of the TVS. And this proposed method can introduce more prior information into the TVS to supply more information. Additionally, under the constraint of prior information, the influence of invalid dimension in the TVS can be weakened. The experimental results show that when the development data is insufficient, the BPCA method can effectively improve the performance compared with the traditional TVS learning methods.关键词：speaker verification;i-vector;total variability space;Bayesian principal component analysis3|16|1更新时间：2025-12-08
- 摘要：A fast set-up and low-noise bandgap reference is designed and implemented with UMC 65nm COMS process. A GΩ level resistor is realized by using a MOS transistor working in deep triode region. Therefore, only a 5pF capacitor is used to realize a switching low-pass filter with a cut-off frequency as low as 32Hz, which effectively reduces the output noise of the bandgap reference. The use of active devices greatly saves chip area and reduces manufacturing costs. A power-on delay circuit is adopted to control the working state of the low-pass filter, which overcomes the problem of slow set-up by using low-pass filters with large resistance or large capacitance capacitors to reduce noise and achieve rapid set-up. The circuit is simulated under 1.8V supply voltage by spectre simulator. The post simulation results show that the output noise of the circuit at 10kHz, 100kHz, and 1MHz are 11.76nV/sqrtHz, 1.213 nV/sqrtHz, 336.8 pV/sqrtHz, respectively. The settling time of the circuit is 1.436μs, and the power consumption is 104.4μW.This design has been applied to the actual chips and achieved the expected effect.关键词：low noise;bandgap reference;fast set-up;low pass filter2|16|1更新时间：2025-12-08
- 摘要：In mobile edge computing (MEC), task offloading can solve the problem of resource constraint on mobile devices effectively, but it is not optimal to offload all tasks to edge servers. In this paper, a multi-user fine-grained task offloading scheduling approach of mobile edge computation is proposed. The computation task is regarded as a directed acyclic graph (DAG), and task nodes’ execution location and scheduling order are optimized. Considering the delay of the system, the computation offloading is considered as a constrained multi-objective optimization problem (CMOP), and an improved NSGA -Ⅱ algorithm is proposed to solve the CMOP. The proposed algorithm can realize local and edge parallel processing to reduce delay. The experimental results show that the algorithm can make the optimal decision in practical applications.关键词：mobile edge computing;computation offloading;constrained multi-objective optimization problem(CMOP);fine-grained task offloading scheduling;NSGA-Ⅱ6|17|4更新时间：2025-12-08
- 摘要：Most of the current constrained many-objective evolutionary algorithms focus on the convergence accuracy, but the convergence speed is relatively slow. In order to improve the convergence speed, a constrained many-objective evolutionary algorithm based on angle information (CMaOEA-AI) is proposed. In the algorithm, a selection operation based on the angle violation function is proposed to improve the convergence speed, which directly selects the superior individuals according to the dynamic convergence and diversity. Thereafter a crossover operation based on the differential evolutionary algorithm is proposed, which can select the infeasible solutions to participate in the crossover operation at different evolutionary stages. Simulation experiments are performed on the standard test function sets C-DTLZ. Compared with four state-of-the-art constrained many-objective evolutionary algorithms, the proposed algorithm shows good convergence accuracy while the convergence speed is greatly improved, and the higher the objective dimension, the better the effect.关键词：constrained many-objective optimization;angle violation function;selection operation;differential evolution algorithm;crossover operation2|17|4更新时间：2025-12-08
- 摘要：In the high-speed motion of the motor car, the bearing of the gearbox is prone to cracks, pitting and other failures. In order to detect the weak fault frequency component in the early stage of fault occurrence, a bearing fault diagnosis method based on wavelet de-noising preprocessing and periodic potential vibration resonance feature-enhancing is proposed. Wavelet packet is used to extract the natural resonance frequency band of the bearing, reconstruct the extracted signal, filter out the interference of the strong noise, and then input the signal into the periodic potential vibration resonance system for enhancing the fault characteristics. Meanwhile, an optimization model considering the amplitude of the high-frequency excitation signal in the vibration excitation system is established, and the ant colony algorithm is used to adaptively optimize the parameters. After obtaining the output signal, it is converted into frequency domain analysis to detect early failure of the bearing. The example analysis shows that the error of the proposed method is reduced to 0.3% compared with the result of stochastic resonance.关键词：gearbox bearings;weak fault signal;wavelet de-noising;periodic potential vibration resonance;ant colony algorithm2|17|2更新时间：2025-12-08
- 摘要：State estimation for jump Markov systems based on multiple models is usually influenced by the quality of model fusion. In this article, we propose a novel state estimation approach for the jump Markov systems based on the maximum mixture correntropy criterion (MMCC). The proposed approach is implemented within the framework of the interacting multiple models. To capture high order information from multiple models, we utilize the MMCC instead of second-order statistical measures at the mixing and fusion stages, respectively. Two cost functions with respect to the system state at different stages are designed and optimized to yield the resultant iterative solutions. Extensive simulated results present the feature of the proposed MMCC based approach, and prove its efficacy for both Gaussian and non-Gaussian cases.关键词：mixture correntropy;state estimation;model uncertainty6|28|1更新时间：2025-12-08
- 摘要：The method based on deep learning has made great progress and good results in solving small faults, but the prerequisite for sufficient sample data is difficult to achieve in the current situation. So there is still a good need for the fault diagnosis method based on traditional data preprocessing. Principal component analysis(PCA) is widely used in fault diagnosis. Because traditional data preprocessing methods use the absolute distance between samples as the criterion for fault detection and fault diagnosis, the feature extraction is not accurate. For this reason, this paper proposes a data preprocessing method based on rate-of-change(ROC) transformation to improve the performance index of PCA in fault diagnosis. After the original data set is preprocessed by the change rate transformation, it can effectively detect the minor faults in the system variables. Finally, the feasibility and effectiveness of the PCA fault diagnosis method based on the rate of data change are verified by simulation.关键词：fault diagnosis;data driven;data preprocessing;gap metric;principal component analysis;rate of change transformation;feature extraction2|17|4更新时间：2025-12-08
- 摘要：In order to improve the perception efficiency and accuracy of autonomous driving vehicles, and to solve the limitations which correspond to the conditions and the multi-source data fusion, this paper advocates a cooperative SLAM(Simultaneous Localization and Mapping) framework for autonomous driving. Firstly, each vehicle runs single SLAM algorithm, builds the local constraints and shares the map and pose. Meanwhile, each vehicle receives and handles data from others. If the coordinate relationship has been established, the coming data is directly fused. Otherwise, the relationship is computed based on the point clouds registration in overlapping areas. The connection components and spawn forest are adopted to track and build the multi-vehicle loop constraint. General Graph Optimization algorithm (G2O) is used to optimize the global map. Experiments based on real world and KITTI dataset show that our framework outperforms relevant SLAM systems, relaxing the conditions of providing relative poses in initial stage and vehicles encountering.关键词：cooperative slam;vehicle-to-vehicle (V2V);data fusion;loop detection;light detection and ranging;autonomous driving5|16|7更新时间：2025-12-08
- 摘要：This paper uses the change of environment library to modulate the coherence evolution of atomic system. The influence of different dynamic modulation forms on the evolution of atomic population is discussed. The modulation forms of the environment center frequency of double Lorentzian reservior are selected as single rectangular pulse, periodic rectangular pulse, combined rectangular pulse and step rectangular pulse. The central frequency of the double Lorentzian environment reservior is modulated by different dynamic environment reserviors, and the coherent evolution of the system is effectively protected and manipulated under the influence of external forces, and the coherence evolution of the controllable quantum state can be better realized. These provide important theoretical basis for the development of quantum devices.关键词：quantum control;spontaneous emission;excited atom2|16|0更新时间：2025-12-08
- 摘要：Secure multi-party computation (MPC) is an important research field of cryptography. Privately computing the k-th minimum element is an important problem of MPC (denoted by k-min problem). MPC protocol for k-min problem can be widely applied to secure voting, secure bid and auction, secure statistical analysis, etc. At present, most solutions to this problem need to repeatedly invoke secure sum protocol and secure comparison protocol. Therefore, the efficiency of the protocols is low. Some solutions designed for mobile network are not applicable to MPC settings. In this paper, we propose a new encoding scheme. Based on this encoding scheme and threshold Lifted ElGamal cryptosystem, we design a simple and efficient MPC protocol for k-min problem. The security of the protocol is strictly proved by using the simulation paradigm and the feasibility of the scheme is proved by the experiment. Using k-min protocol as a building block, we further design a protocol for privacy-preserving score statistics and sorting. Theoretical analysis and experimental result show that our protocols are secure and efficient.关键词：secure multi-party computation;k-min problem;privacy-preserving score statistics and sorting;homomorphic encryption;security2|23|0更新时间：2025-12-08
PAPERS
- 摘要：Full reference image quality assessment (FR-IQA) is one of the types widely studied in the field of IQA. This paper reviews the development of FR-IQA, summarizes the application status of FR-IQA and the construction of general FR-IQA problems, and summarizes and combs FR-IQA algorithms. And on this basis, it focuses on the problems existing in the existing research, including the rationality of the problem construction, the comprehensive problem of modeling, and the problem of the combination of knowledge-driven and data-driven. Finally, based on the in-depth analysis of the subjective evaluation process and the existing problems in the existing research, the two possible research directions of subjective scoring using fuzzy modeling and knowledge-data-driven construction algorithm are discussed, in order to provide reference for subsequent researchers.关键词：image quality assessment;FR-IQA;subjective rating;fuzzy modeling;knowledge-data joint driven2|15|6更新时间：2025-12-08
SURVEYS AND REVIEWS
- 摘要：Given a source stop and a destination stop in a transportation timetable, the route planning query returns a Pareto set of paths that optimized in both earlier arrival time and less transfer times. Current indexing methods require large runtime memory. This paper proposes a memory space efficient index method (a-)PAINT. (a-)PAINT pre-computes, for each stop v, a set of labels, such that, for any query from stop s to stop d, we can efficiently retrieve a path of the query result from the label sets of s and d. PAINT could return optimal paths for every query. a-PAINT incurs far less preprocessing overheads, but might return sub-optimal path that takes one more transfer. We experimentally conducted simulated queries on real timetables. PAINT incurs reasonable preprocessing overheads. a-PAINT requires far less preprocessing overheads, and it has accurate rate up to 90% in large timetables.关键词：route planning;index;public transportation network;timetable;transfer times5|17|0更新时间：2025-12-08
- 摘要：Based on the idea to integrate the dynamic idea into the block cipher design to make the algorithm have dynamic performance and to improve the anti-attack ability, CLEFIA-like dynamic cryptographic structure is put forward in this paper. By establishing the relation between differential correspondences of two classes of cryptographic structures, the ability of CLEFIA-like dynamic cryptographic structure to resist differential cryptanalysis is given. Concretely, for 4r(r≥1)-round CLEFIA-like dynamic cryptographic structure, if the round functions are all bijective, then the number of active round functions for l-round differential characteristic is not less than l-1.关键词：CLEFIA-like dynamic cryptographic structure;differential cryptanalysis;active round functions4|15|4更新时间：2025-12-08
- 摘要：Cyclic codes and linear complementary dual (LCD) codes are two important classes of linear codes which have been extensively used in data storage systems, communication systems and cryptography. In this paper, LCD cyclic codes over
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