An Improved Gaussian Mixture CKF Algorithm under Non-Gaussian Observation Noise by Hongjian Wang, Cun Li

“…The algorithm adopts Gaussian mixture density function to approximately estimate the observation noise. …”
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Study on the SOVA decoding algorithm for Turbo codes based on modified path-metric by LIU Xing-cheng, ZHU Zhi

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Ultra-Short Wave Communication Squelch Algorithm Based on Deep Neural Network by Yuanxin Xiang, Yi Lv, Wenqiang Lei, Jiancheng Lv

“…To alleviate the problem, we proposed a squelch algorithm for ultra-short wave communication based on a deep neural network and the traditional energy decision method. …”
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Research on meaningful image encryption algorithm based on 2-dimensional compressive sensing by Hua REN, Shaozhang NIU, Ruyong REN, Zhen YUE

“…Aiming at the problems that the existing compressive sensing-based meaningful image encryption algorithms have low visual security of the encrypted images and poor quality of the reconstructed images, a 2-dimensional compressive sensing-based (2DCS) meaningful image encryption algorithm was proposed.Firstly, a chaotic pseudo-random sequence generation method associated with plaintext was designed, and the global random permutation and grayscale transformation operations were used for pre-encryption to improve the decrypted image quality.The generated pre-encrypted image was used as the input for 2DCS, and the secret image was generated after the compression encryption and quantization operations.Secondly, the relationship between the hidden and the modified data was considered, and an adaptive embedding method was adopted to modify the carrier coefficient values to improve the visual security of meaningful encrypted image.Finally, the 2-dimensional projection gradient reconstruction method was adopted to decompress and decrypt to obtain the decrypted image.The experimental results show that, compared with the existing algorithms, the proposed algorithm not only improves the visual security of encrypted image and the quality of reconstructed image, but also can resist noise and cropping attacks.…”
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Hole recovery algorithm based on mobile inner nodes in wireless sensor networks by Kai YANG, Quan LIU, Shu-kui ZHANG, Jin LI, Dong-liang WENG

“…To solve the problem of coverage holes in target areas,a principle for hole recovery was proposed.Based on the principle,a novel algorithm named SOI was proposed for hole recovery using mobile nodes,which does not require location information,figures out the optimal inner nodes in the edge of coverage holes,and then moves them to new po-sitions.Through this mechanism,the area of coverage holes could be reduced.Analysis and simulation results show that,SOI has a better performance in dense deployed wireless sensor networks compared with existing VHR algorithm.…”
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Statistical ineffective fault analysis of the lightweight authenticated cipher algorithm Saturnin-Short by Wei LI, Chun LIU, Dawu GU, Wenqian SUN, Jianning GAO, Mengyang QIN

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Joint sparse model based data reconstruction algorithm for wireless sensor network by Yi-yin LIU, Guo-rui LI, Li TIAN

“…The data of wireless sensor network has strong joint sparse characteristics,by utilizing compressed sensing theory,compressed data by joint encoding,and then reconstructed the data by joint decoding,the sensed data can be gathered with low computational cost.A synchronous subspace pursuit algorithm based on joint sparse model and com-pressed sensing theory was proposed.By utilizing the sparsity of the sensed data,it selected the correct joint subspace and reconstruct the original signal group accurately with fewer observations in a backtracking iterative manner.Com-pared with SCoSaMP algorithm and SP algorithm,the proposed algorithm presents better data reconstruction perform-ance under the conditions of different sparsity and sampling rate.…”
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Novel Registration and Fusion Algorithm for Multimodal Railway Images with Different Field of Views by Baoqing Guo, Xingfang Zhou, Yingzi Lin, Liqiang Zhu, Zujun Yu

“…In order to improve accuracy of railway intrusion detection, an automatic multimodal registration and fusion algorithm for infrared and visible images with different field of views is presented. …”
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A range spread target detection algorithm based on polarimetric features and SVDD by Qiang LI, Yuanxin YAO, Xiangqi KONG

“…Multi-polarization range high resolution radar is an important mean for ground target detection.In the echo formed by it, the target occupies multiple range cells and becomes an extended target.The traditional spread target detection method relies on energy, and the detection performance decreases when the signal-to-clutter ratio decreases.A spread target detection algorithm based on polarization decomposition features was proposed, which improved the detection performance under low signal-to-clutter ratio by using the difference of polarization scattering characteristics between target and clutter.Specifically, 16 kinds of polarization decomposition features were extracted to form feature vectors as detection statistics, and then support vector data description (SVDD) was used to obtain the detection threshold.When training the detection threshold, the polarization decomposition features of clutter were extracted as training data.In order to ensure the false alarm probability, two penalty parameters were introduced into the objective function of SVDD.The experimental results show that the proposed method requires a signal-to-clutter ratio of about 12.6 dB in the case of Gobi background, false alarm probability of 10^-4 and detection probability of 90%, which is about 1.7 dB lower than the energy-based methods.…”
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Research on Enterprise Supply Chain Optimization Model and Algorithm Based on Fuzzy Clustering by Shizhen Bai, Hongbin Sun

“…Because the single-level distribution network structure of production enterprises is not suitable for large-scale logistics distribution, this paper proposes a distribution network structure design that accords with economies of scale and establishes an enterprise supply chain optimization model based on the fuzzy clustering algorithm. Using this optimization method to optimize the inventory of enterprise logistics supply chain, the operation is fast, the result is correct and reasonable, and it can provide good decision support for the distribution network of logistics enterprises. …”
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Step-by-step classification detection algorithm of SPPM based on K-means clustering by Huiqin WANG, Wenbin HOU, Qingbin PENG, Minghua CAO, Rui HUANG, Ling LIU

“…In view of the high computational complexity in spatial pulse position modulation systems when using maximum likelihood detection algorithm, a step-by-step classification detection algorithm based on K-means clustering was proposed according to the characteristics of signal matrix with spatial pulse position modulation.The signal vector detection algorithm was utilized to detect the index of light source in the training samples.The on K-means clustering algorithm was utilized to acquire the mapping rule between centroid of samples and modulated symbol by offline training.Subsequently, online detection of modulated symbols was achieved based on the mapping rule, and then the index of light sources was detected by exhaustive search.In addition, Monte Carlo method was used to investigate the effects of key parameters such as the number of clusters and initialization times on the system bit error rate (BER) performance.Simulation results demonstrate that the proposed algorithm can achieve an approximate BER performance as the maximum likelihood algorithm on the basis of greatly reducing the computational complexity.Compared with the linear decoding algorithms, the proposed algorithm is also applicable to scenarios where the number of detectors is less than the number of light sources.…”
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Advancing semantic segmentation: Enhanced UNet algorithm with attention mechanism and deformable convolution. by Effat Sahragard, Hassan Farsi, Sajad Mohamadzadeh

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Q-learning based handoff algorithm for satellite system with ancillary terrestrial component by Dan-ni XIONG, Yi LI

“…,mobile satellite system with ancillary terres-trial component (MSS-ATC),the long transmission delay of satellite link was a huge challenge which may lead to high handoff dropping probability.In order to address this problem,a novel handoff decision strategy was proposed based on the predictive RSS and Q-learning algorithm.Extensive simulation results demonstrate that the proposed scheme can de-crease the handoff dropping probability,reduce the unnecessary handoff times and maximize the network reward.In ad-dition,the proposed scheme can also adapt to the situation of high-speed movement very well.…”
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Modified kernels-alternated error diffusion multipurpose watermarking algorithm for halftone images by NI Jiang-qun1, XIE Zhen1, TANG Lin-na1, HUANG Ji-wu1

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An Energy-Balanced Path Planning Algorithm for Multiple Ferrying UAVs Based on GA by Lisong Wang, Xiaoliang Zhang, Pingyu Deng, Jiexiang Kang, Zhongjie Gao, Liang Liu

“…Based on the genetic algorithm, we design and implement an energy-balanced path planning algorithm (EMTSPA) for multiple ferrying UAVs to solve this multiobject optimization problem. …”
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Minimum number oriented relay node deployment algorithm in two-tiered WSN by Chun-yu MIAO, Li-na CHEN, Guo-yong DAI, Fan YANG, Qing-zhang CHEN

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Fuzzy Logic Controller Based on Genetic Algorithm for Electric Drive of Crane Trolley by S. E. Alavi, I. N. Petrenko

“…The paper describes a methodology based on the genetic algorithm that permits to automate the process for obtaining optimum rule bases while applying a controller based on a fuzzy logic. …”
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Identification of Optimal Path in Power System Network Using Bellman Ford Algorithm by S. Hemalatha, P. Valsalal

“…In this paper, the Bellman Ford Algorithm (BFA) is applied to find out the optimal path and also the several alternative paths by considering all the constraints. …”
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Design and Optimization of Trapezoidal Steering Mechanism based on Improved Particle Swarm Algorithm by Jianhua Zhai, Laiqi Qiu, Xiaohua Wei, Dongshan Yang

“…The traditional particle swarm optimization algorithm is introduced into the adaptive weights and Lagrange interpolation method to improve the algorithm. …”
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Spectrum allocation algorithm based on multi-agent reinforcement learning in smart grid by Feng YAN, Xiaowei LIN, Zhenghao LI, Xia XU, Weiwei XIA, Lianfeng SHEN

“…In view of the fact that 5G networks are used to meet the service requirements of various power terminals in smart grid, a spectrum allocation algorithm based on multi-agent reinforcement learning was proposed.Firstly, for the integrated access backhaul system deployed in smart grid, considering the different communication requirements of services in lightweight and non-lightweight terminal, the spectrum allocation problem was formulated as a non-convex mixed-integer programming aiming to maximize the overall energy efficiency.Secondly, the above problem was modeled as a partially observable Markov decision process and transformed into a fully cooperative multi-agent problem, then a spectrum allocation algorithm was proposed which was based on multi-agent proximal policy optimization under the framework of centralized training and distributed execution.Finally, the performance of the proposed algorithm was verified by simulation.The results show that the proposed algorithm has a faster convergence speed and can increase the overall transmission rate by 25.2% through effectively reducing intra-layer and inter-layer interference and balancing the access and backhaul link rates.…”
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