Quantitative Detection of Financial Fraud Based on Deep Learning with Combination of E-Commerce Big Data by Jian Liu, Xin Gu, Chao Shang

“…At the same time, in order to reduce the computational complexity, the feature extraction is restricted to the space-time volume of the dense trajectory. …”
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Improved Algorithm for Gradient Vector Flow Based Active Contour Model Using Global and Local Information by Jianhui Zhao, Bingyu Chen, Mingui Sun, Wenyan Jia, Zhiyong Yuan

“…Experimental results illustrate the efficiency of our method, and the computational complexity is also analyzed.…”
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Research and optimization on the sensing algorithm for 6G integrated sensing and communication network by Xiaoyun WANG, Xiaozhou ZHANG, Liang MA, Yajuan WANG, Mengting LOU, Tao JIANG, Jing JIN, Qixing WANG, Guangyi LIU

“…High-precision sensing is one of the basic capabilities of 6G mobile communication system to fulfill the demands of many application scenarios in the future, and the integrated design of sensing and communication (ISAC) is an important direction of 6G research.The works on ISAC mainly focus on improving the sensing performance.However, besides high sensing accuracy, 6G ISAC network still has a high communication rate requirement.Therefore, joint analysis and design of communication and sensing is necessary.First, three classic sensing algorithms were introduced that could achieve multi-target ranging and speed measurement, and the algorithms were analyzed from three aspects: sensing accuracy, communication performance and computational complexity.It is shown that the optimal sensing accuracy, sensing capacity and communication rate could not be achieved at the same time by using either one algorithm.Second, combined with the characteristics of different sensing algorithms, an adaptive sensing algorithm was proposed that the receiver selected the appropriate sensing algorithm according to the measured receive signal-to-interference-plus-noise ratio to realize the joint optimization of sensing and communication performance.Finally, the link-level simulation was carried out to verify that the proposed algorithm can obtain better sensing accuracy and communication capacity than any single algorithm.…”
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Fast blind detection of short-wave frequency hopping signal based on MeanShift by Zhengyu ZHU, Yu LIN, Zixuan WANG, Kexian GONG, Pengfei CHEN, Zhongyong WANG, Jing LIANG

“…In the complex short-wave channel environment, combined with time-frequency analysis technology, a fast blind detection algorithm of the connected domain labeled frequency hopping signals based on MeanShift algorithm was proposed to reduce the influence of various interference signals and noises on frequency hopping signals and realize blind detection of frequency hopping signals under low signal-to-noise ratio.Firstly, the channel environment gray-scale time-frequency map was filtered by the secondary gray-scale morphology to obtain the binary time-frequency map.Secondly, the maximum duration of the signal was calculated by the connected domain labeling algorithm.Then, the MeanShift algorithm was used to cluster the maximum duration of the signal.Finally, the clustering result was made a second judgment by combining with the adaptive double threshold.The simulation results show that the proposed algorithm can quickly separate various interference signals and sharp noise under low signal-to-noise ratio, and realize fast blind detection of frequency hopping signals without any prior information.It has high detection probability, strong anti-interference ability in short-wave channel environment, low computational complexity and high engineering practical value.…”
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Joint Subchannel Pairing and Power Control for Cognitive Radio Networks with Amplify-and-Forward Relaying by Yanyan Shen, Shuqiang Wang, Zhiming Wei

“…To reduce the computational complexity, two suboptimal algorithms are developed. …”
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Fast copy-move forgery detection algorithm based on group SIFT by Bin XIAO, Ruxia JING, Xiuli BI, Jianfeng MA

“…Aiming at the high computational complexity of the existing copy-move image forgery detection algorithm,a copy-move forgery detection algorithm based on group scale-invariant feature transform (SIFT) was proposed.Firstly,the simple linear iterative clustering (SLIC) was utilized to divide the input image into non-overlapping and irregular blocks.Secondly,the structure tensor was introduced to classify each block as flat blocks,edge blocks and corner blocks,and then the SIFT feature points extracted from the block were taken as the block features.Finally,the forgery was located by the inter-class matching of the block features.By means of inter-class matching and feature point matching,the time complexity of the proposed copy-move forgery detection algorithm in feature matching and locating forgery region was effectively reduced while guaranteeing the detection effect.The experimental results show that the accuracy of the proposed algorithm is 97.79%,the recall rate is 90.34%,and the F score is 93.59%,the detecting time for the image with size of 1024×768 is 12.72 s,and the detecting time for the image with size of 3000×2000 was 639.93 s.Compared with the existing copy-move algorithm,the proposed algorithm can locate the forgery region quickly and accurately,and has high robustness.…”
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EMIKNet: Expanding Multiple-Instance Inverse Kinematics Network for Multiple End-Effector and Multiple Solutions by Youn-Jae Go, Jun Moon

“…Inverse Kinematics (IK) is essential for robot control but suffers from computational complexity as the number of links and end-effectors increases, thereby affecting real-time control accuracy and performance. …”
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Computationally Efficient Compressed Sensing-Based Method via FG Nyström in Bistatic MIMO Radar with Array Gain-Phase Error Effect by Jurong Hu, Evans Baidoo, Lei Zhan, Ying Tian

“…Additionally, the analyses of the computational complexity and the Cramér–Rao bounds for angle estimation are derived theoretically. …”
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Unmanned aerial vehicle aerial image stitching method based on superpixel segmentation by Zhiyou Lian, Jianhua Ren

“…Abstract Addressing the issues of long processing time, high computational complexity, and poor stitching quality in existing methods for unmanned aerial vehicle (UAV) aerial image stitching, this paper proposes an aerial image stitching method based on similar region estimation. …”
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Two-Dimensional Direction-of-Arrivals Estimation Based on One-Dimensional Search Using Rank Deficiency Principle by Feng-Gang Yan, Zhi-Kun Chen, Ming-Jian Sun, Yi Shen, Ming Jin

“…A novel efficient method for two-dimensional (2D) direction-of-arrivals (DOAs) estimation is proposed to reduce the computational complexity of conventional 2D multiple signal classification (2D-MUSIC) algorithm with uniform rectangular arrays (URAs). …”
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An Improved Multicell MMSE Channel Estimation in a Massive MIMO System by Ke Li, Xiaoqin Song, M. Omair Ahmad, M. N. S. Swamy

“…Conventional channel estimation schemes cannot mitigate this problem effectively, and the computational complexity is increasingly becoming larger in views of the large number of antennas employed in a massive MIMO system. …”
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Early Merge mode decision algorithm for 3D-HEVC based on learning model by Yue LI, Gaobo YANG, Xiangling DING, Yapei ZHU

“…3D-high efficiency video coding (3D-HEVC) standard is an extension of HEVC.Though 3D-HEVC effectively improves the compression efficiency of 3D video,it also brings huge computational complexity.To greatly reduce the 3D-HEVC coding complexity,an early Merge mode decision approach was proposed.The residual signal that encoded by the Merge mode was firstly extracted as feature information.A learning model was established in terms of the residual signals of the coding unit (CU) in current frame that used early Merge mode as the optimal mode.Finally,the residual signal was extracted for the Merge mode of current CU,and the learning model was used to predict whether the Merge mode was the optimal mode or not.Experimental results show that the proposed early Merge mode decision approach reduces the coding times of 3D-HEVC texture views and depth maps about 41.9% and 24.3%,respectively,and the coding performance degradation is almost negligible.Compared with existing early Merge mode decision approaches,the proposed approach further reduces the coding time,and can be easily integrated into the 3D-HEVC test model due to its design simplicity.…”
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Distributed filtering in sensor networks based on linear minimum mean square error criterion with limited sensing range by Teng Shao

“…The stability and computational complexity of linear minimum mean square error filter are analyzed. …”
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DCFE-YOLO: A novel fabric defect detection method. by Lei Zhou, Bingya Ma, Yanyan Dong, Zhewen Yin, Fan Lu

“…Finally, the feature fusion network integrates Partial Convolution and Efficient Multi-scale Attention, optimizing the fusion of information across different feature levels and spatial scales, which enhances the richness and accuracy of feature representations while reducing computational complexity. Experimental results demonstrate a significant improvement in detection performance. …”
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A multi-band spectrum sensing method based on sticky hidden Markov model by Zhongjie JIA, Ming JIN, Xiaoqun SONG

“…Existing multi-band spectrum sensing methods often use the sparsity of broadband spectrum.However, high spectrum occupancy rate of primary users degrades their performance severely.To address this issue, a novel multi-band spectrum sensing method was proposed by exploiting the state correlation among adjacent frequency bands.Firstly, a sticky hidden Markov model (SHMM) was established by regarding the multi-band states and measured energies as hidden and observed variables.In the SHMM, a sticky factor was introduced to represent the state correlation among adjacent frequency bands.Secondly, iterative expressions for the parameters of SHMM were derived.Finally, multi-band spectrum sensing was implemented by obtaining the posterior mean of observations from every frequency bands.Simulation results show that the proposed method outperforms existing methods, and when the false alarm probability is 0.1, the average frequency band occupancy rate is 50%, and the average signal-to-noise ratio is -12 dB, the detection probability can reach close to 0.99, which is about 30% higher than the detection probability of other methods.In addition, the proposed method had a faster convergence rate than existing methods and therefore has lower computational complexity.…”
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A Novel SLM Scheme for PAPR Reduction in OFDM Systems by Tian-Ming Ma, Yu-Song Shi, Ying-Guan Wang

“…The complexity analysis and simulation results show that this algorithm can dramatically reduce computational complexity comparing with the conventional SLM scheme as in Hill et al., 2000; Yang et al., 2009; Wang and Ouyang, 2005; Li et al., 2010; and Heo et al., 2007 under the similar PAPR reduction performance.…”
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A Fast Adaptive Receive Antenna Selection Method in MIMO System by Chaowei Wang, Weidong Wang, Cheng Wang, Shuai Wang, Yang Yu

“…Mathematical analysis and numerical results show that our algorithm significantly reduces the computational complexity and memory requirement and achieves considerable system capacity gain compared with the optimal selection technique in the same time.…”
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Efficient Pruning of Detection Transformer in Remote Sensing Using Ant Colony Evolutionary Pruning by Hailin Su, Haijiang Sun, Yongxian Zhao

“…This study mainly addresses the issues of an excessive model parameter count and computational complexity in Detection Transformer (DETR) for remote sensing object detection and similar neural networks. …”
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Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method by Rasim M. Alguliyev, Ramiz M. Aliguliyev, Rasmiyya S. Mahmudova

“…Firstly, from a computational complexity point of view, the presented model is effective. …”
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Personalized Recommendation Model of High-Quality Education Resources for College Students Based on Data Mining by Chaohua Fang, Qiuyun Lu

“…Currently, most learner models generally have a lack of scientific focus that they have a single method of obtaining dimensions, feature attributes, and low computational complexity. These problems may lead to disagreement between the learner’s learning ability and the difficulty of the recommended learning resources and may lead to the cognitive overload or disorientation of learners in the learning process. …”
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