Improved transmit beamforming design based on ADMM for low probability of intercept of FDA-MIMO radar by Pengcheng GONG, Yuntao WU

“…Considering the low probability of intercept problem that the signal-dependent interference and the target were located in the same angle, an improved transmit beamforming design based on the alternating direction method of multipliers (ADMM) was proposed for multiple-input multiple-output with frequency diverse array radar.The transmit energy was minimized at the target under constraints of the energy at each transmitter and signal clutter-plus-noise ratio requirement.Subsequently, a cyclic algorithm was developed to tackle the non-convex design problem.Firstly, the optimal receive filter was obtained by generalized Rayleigh quotient.And then the transmit beamforming was optimized by employing auxiliary variables and ADMM to solve quadratic programming problem with fractional inequality constraint.Moreover, both the convergence and computational complexity of the proposed algorithm were discussed.Simulation results show that, compared with the semi-denite programming method, the proposed method not only attains the given antenna power, but also achieves the better mainlobe focusing performance at the target.Furthermore, the null levels at the clutter locations and the jamming directions obtained by the proposed method are -50 dB above.…”
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A low-delay information sharing algorithm for multiple-radio-per-platform networking by Ge Lin, Xu Renhui, Peng Laixian, Li Aijing, Yang Yaoqi

“…In order to ensure the strong real-time information sharing of Aerial Ad hoc Network, a low-delay information sharing algorithm for multiple-radio-per-platform networking is proposed based on the directional transmission capability of phased-array antenna. …”
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Low complexity hybrid iterative algorithm based signal detection in massive MIMO system by Shufeng ZHAO, Bin SHEN, Furong YANG

“…Among the uplink signal detection algorithms for massive MIMO systems,the minimum mean square error (MMSE) algorithm can achieve the near-optimal linear detection performance.However,conventional MMSE usually involves high complexity due to the required matrix inversion of large-size matrix,which makes it hard to implement in realistic applications.Based on joint steepest descent (SD) algorithm and Gauss-Seidel iteration,a low complexity hybrid iterative detection algorithm was proposed.The SD algorithm was employed to obtain an efficient searching direction for the following Gauss-Seidel to speed up convergence.Meanwhile,an approximated method was also proposed to compute the bit log-likelihood ratio (LLR) for soft channel decoding.Simulation results verify that the proposed algorithm can converge rapidly and achieve its performance quite close to that of the MMSE algorithm with only a small number of iterations.Meanwhile,the complexity is reduced by an order of magnitude,which is kept consistently of O(K ²).…”
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The DOA Estimation Algorithm Based on Virtual Domain Block Matching for Nested Arrays in the Presence of Mutual Coupling by Shun He, Nan Sun, Zhiwei Yang, Le Qin

“…Using algorithms to reduce it is an effective approach. Few algorithms are suitable for nested arrays, and due to incomplete elimination or the loss of some data, they performance deteriorates in the small number of snapshot and low signal-to-noise ratio environments. …”
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Off-grid DOA estimation algorithm based on unitary transform and sparse Bayesian learning by Yang GAO, Jun-li CHEN, Guang-li YANG

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Low-carbon economic dispatching of integrated energy system based on improved white shark algorithm by LI Haobo, CUI Shuangxi, FAN Weijie

“…The white shark algorithm is improved by integrating directed differential mutation and other strategies to solve the low-carbon economic scheduling model of the integrated energy system, and the optimal scheduling scheme of each time period is obtained by combining the advantages and disadvantages of the solution distance method. …”
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Denoising MEMS accelerometer sensors based on L2‐norm total variation algorithm by R. Abbasi‐Kesbi, A. Nikfarjam

“…A method for denoising accelerometer data based on the L2‐norm total variation (LTV) algorithm is presented. In order to collect accelerometer data, a wireless accelerometer sensor was developed that is directly connected to a central node. …”
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Progress and future direction of independently developed reservoir numerical simulation software in Shengli Oilfield by ZHANG Zhiqiang, YANG Yaozhong, ZHANG Shiming, YU Jinbiao, CAO Weidong, HU Huifang

“…The software demonstrates significant technical advantages in simulating differentiated oil-water flow at ultra-high water-cut stages and nonlinear flow in low-permeability reservoirs. Furthermore， by establishing efficient mathematical model discretization and solution algorithms， such as decoupling sequencing， alternating direction， adaptive grids， and algebraic multigrid methods， the software achieves rapid solutions for reservoir models with millions to tens of millions of grid cells， largely meeting the needs of field development planning. …”
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Low-Cost Direct Digital Synthesis-Based On-Chip Waveform Generation for Analog/Mixed Signal BIST Applications by Emmanuel Nti Darko, Isaac Bruce, Ekaniyere Oko-Odion, Kushagra Bhatheja, Saeid Karimpour, Degang Chen

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Enhanced Magnetic Wireless Sensor Network Algorithm for Traffic Flow Monitoring in Low-Speed Congested Traffic by Haji Said Fimbombaya, Nerey H. Mvungi, Ndyetabura Y. Hamisi, Hashimu U. Iddi

“…One of the challenges facing such deployment is the development of effective detection signal-processing algorithm in low-speed congested traffic based on the Earth’s magnetic fields. …”
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Loss reduction optimization strategies for medium and low-voltage distribution networks based on Intelligent optimization algorithms by Nian Liu, Yuehan Zhao

“…Methodology In order to reduce line losses, a loss optimization model for low and medium voltage distribution networks based on an improved Gray Wolf optimization support vector machine is proposed. …”
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An Unambiguous Super-Resolution Algorithm for TDM-MIMO-SAR 3D Imaging Applications on Fast-Moving Platforms by Sheng Guan, Mingming Wang, Xingdong Liang, Yunlong Liu, Yanlei Li

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A Low Complexity Subspace-Based DOA Estimation Algorithm with Uniform Linear Array Correlation Matrix Subsampling by Do-Sik Yoo

“…We propose a low complexity subspace-based direction-of-arrival (DOA) estimation algorithm employing a direct signal space construction method (DSPCM) by subsampling the autocorrelation matrix of a uniform linear array (ULA). …”
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Comparing Machine Learning Algorithms to Enhance Volumetric Water Content Prediction in Low-Cost Soil Moisture Sensor by Iman Setiawan, Mohammad Dahlan Th. Musa, Dini Aprilia Afriza, Siti Nur Hafidah

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Cross-domain subcortical brain structure segmentation algorithm based on low-rank adaptation fine-tuning SAM by Yuan Sui, Qian Hu, Yujie Zhang

“…Deep learning foundation models trained and designed on large-scale natural scene image datasets experience significant performance degradation when applied to subcortical brain structure segmentation in MRI, limiting their direct applicability in clinical diagnosis. Methods This paper proposes a subcortical brain structure segmentation algorithm based on Low-Rank Adaptation (LoRA) to fine-tune SAM (Segment Anything Model) by freezing SAM’s image encoder and applying LoRA to approximate low-rank matrix updates to the encoder’s training weights, while also fine-tuning SAM’s lightweight prompt encoder and mask decoder. …”
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Reliability growth model of quantum direct current electricity meter software based on optimization network by TIAN Teng, QIU Rujia, ZHAO Long, GENG Jiaqi, WANG Enhui, SUN Yu

“…In the past, when several types of commonly-used neural networks were used for modeling, there were problems like low parameter training efficiency and low generalization ability caused by unsatisfactory parameters, which reduced the prediction accuracy of the models to a certain extent. …”
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On-board Multi-User Detection Algorithm Based on Conditional Neural Process by Yilun LIU, Liang JIN, Jiali LI, Lidong ZHU

“…With the characteristics of all-terrain, all-weather and seamless coverage, satellite communications have become a potentially important part of 6G.An important prerequisite for achieving satellite intelligence is that the satellite have on-board processing capabilities.Multi-user detection (MUD) is a classic method of suppressing multiple access interference (MAI) in wireless communication, such as MMSE, Gaussian processregression (GPR) and other algorithms.Due to the inverse matrix required in the detection process, the algorithm complexity is usually cubic, and it is diff cult to directly apply to satellite platforms because of its limited processing capabilities.The conditional neural process combined the characteristics of the low complexity of the neural network and the data-eff cient of the Gaussian process.The neural network was used to parameterized the Gaussian process to avoided the inversion of the matrix, thereby reduced the computational complexity.The application of conditional neural process in MUD was studied.The simulation results showed that, while reduced complexity, conditional neural process also greatly improved the performance of bit error rate (BER).…”
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Direction of Arrival (DOA) Estimation Using a Deep Unfolded Learned Iterative Shrinkage Thresholding Algorithm (LISTA) Network in a Non-Uniform Metasurface by Xinyi Niu, Xiaolong Su, Lida He, Guanchao Chen

“…Simulation results prove that this method enhances higher precision and reduces computational complexity in comparison with traditional algorithms, especially under low SNR conditions. Furthermore, the method exhibits greater generalization ability, making it a reliable approach for high-precision DOA estimation in practical applications.…”
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Hierarchical Multi-UAV Path Planning for Urban Low Altitude Environments by Haoxiang Lei, Yuehao Yan, Jilong Liu, Qiang Han, Zhouguan Li

“…Aiming at the demand of multi-UAV missions in urban low-altitude environment, combined with the concept of low-altitude economy, the urban environment is divided into multiple layers in the vertical direction to accomplish path planning. …”
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A Sequential Generation Redispatch Algorithm to Ensure Power System Small Signal Stability under Low-Frequency Oscillations by Hassan Golzari-Kolur, Seyed Mohammad-Taghi Bathaee, Turaj Amraee

“…The redispatch model is solved using the quadratic programming algorithm, and the Newton algorithm is used to manage the nonlinear and nonconvex characteristics of the power flow model. …”
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