Hybrid precoding method for mmWave massive MIMO systems based on LFM by Haoyi CHEN, Yifan DING, Ying CHENG

“…Analog-digital hybrid precoding is a key technology for millimeter wave massive MIMO systems that reduce hardware costs while balancing system performance.However,the traditional hybrid precoding scheme often needed to find a suitable codebook for precoding,and some codebooks were not easy to obtain or had deviations in actual situations.An analog-digital hybrid precoding method based on latent factor model (LFM) in machine learning without codebook was proposed for this problem.The LFM decomposition and stochastic gradient descent method were used to approximate the designed precoding matrix to the optimal full digital precoding matrix for good performance.The simulation results show that compared with the hybrid precoding design method based on orthogonal matching pursuit (OMP) algorithm,this method not only does not need a codebook,but also has better performance than the hybrid precoding algorithm based on OMP algorithm,which is closer to optimal full digital precoding method.…”
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Deep neural networks have an inbuilt Occam’s razor by Chris Mingard, Henry Rees, Guillermo Valle-Pérez, Ard A. Louis

“…For Boolean function classification, we approximate the likelihood using the error spectrum of functions on data. …”
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Disease Spread in Coupled Populations: Minimizing Response Strategies Costs in Discrete Time Models by Geisel Alpízar, Luis F. Gordillo

“…In both examples we compute approximations for the control levels necessary to minimize costs and quickly contain outbreaks. …”
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Adaptive Finite-Time Fault-Tolerant Control for Half-Vehicle Active Suspension Systems with Output Constraints and Random Actuator Failures by Jie Lan, Tongyu Xu

“…Unknown functions and coefficients are approximated by the neural network (NN). Assisted by the stochastic practical finite-time theory and FTC theory, the proposed controller can ensure systems achieve stability in a finite time. …”
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Dimension reduction for maximum matchings and the Fastest Mixing Markov Chain by Jain, Vishesh, Pham, Huy, Vuong, Thuy-Duong

“…We show that there exists a symmetric, stochastic matrix $P$, with off-diagonal entries supported on $E$, whose spectral gap $\gamma ^*(P)$ satisfies \[ \Psi ^*(G)^{2}/\log \Delta \lesssim \gamma ^*(P) \lesssim \Psi ^*(G). \] Our bound is optimal under the Small Set Expansion Hypothesis, and answers a question of Olesker-Taylor and Zanetti, who obtained such a result with $\log \Delta $ replaced by $\log |V|$.In order to obtain our result, we show how to embed a negative-type semi-metric $d$ defined on $V$ into a negative-type semi-metric $d^{\prime }$ supported in $\mathbb{R}^{O(\log \Delta )}$, such that the (fractional) matching number of the weighted graph $(V,E,d)$ is approximately equal to that of $(V,E,d^{\prime })$.…”
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PRIMARY RESONANCE ANALYSIS OF ARM SYSTEM UNDER BOUNDED NARROW⁃BAND EXCITATION by YANG ZhiAn, MAN ZhiJun, LIU WenYang

“…By using multi⁃scales method,the first primary resonance of the human arm and vibration mechanical coupling system under random narrow⁃band excitation was analyzed,and the two⁃degree⁃of⁃freedom nonlinear dynamic equation of the arm system was established.The first primary resonance amplitude frequency response equation and Ito stochastic differential equation of the system were solved in turn.In order to study the distribution law of variables under random vibration,the approximate expressions of the expectation and mean square value of the first primary resonance random mean square response were calculated using the moment estimation method.The influence of the parameters of the human arm system on the primary resonance was obtained through numerical analysis.The results show that the mean square response curves of the first primary resonance have the same topological structure as their amplitude⁃frequency response curves,and the mean square value of the primary resonance amplitudes and the resonance region increase with the increase of the amplitude of the external excitation,while the increase of the system damping will reduce the mean square value and the resonance region.The change of nonlinear stiffness coefficient has little effect on the system.…”
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Mathematical and statistical approaches in epidemiological investigation of hospital infection: A case study of the 2015 Middle East Respiratory Syndrome outbreak in Korea. by Youngsuk Ko, Eunok Jung

“…Mary's Hospital, the Republic of Korea. We developed a stochastic model based on individual case data to derive a likelihood function for disease transmission. …”
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Bias Errors due to Leakage Effects When Estimating Frequency Response Functions by Andreas Josefsson, Kjell Ahlin, Göran Broman

“…In this paper the bias error in the H1 and H2-estimate is studied and a new method is proposed to derive an approximate expression for the relative bias error at the resonance frequency with different window functions. …”
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A Grey NGM(1,1,k) Self-Memory Coupling Prediction Model for Energy Consumption Prediction by Xiaojun Guo, Sifeng Liu, Lifeng Wu, Lingling Tang

“…Although there are several prediction techniques, selection of the most appropriate technique is of vital importance. As for the approximate nonhomogeneous exponential data sequence often emerging in the energy system, a novel grey NGM(1,1,k) self-memory coupling prediction model is put forward in order to promote the predictive performance. …”
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Convergence Speed of Bermudan, Randomized Bermudan, and Canadian Options by Guillaume Leduc

“…However, theoretical results regarding the speed of convergence of these approximations to the American option price remain scarce. …”
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Learning a Quantum Computer's Capability by Daniel Hothem, Kevin Young, Tommie Catanach, Timothy Proctor

“…Our CNN capability models obtain approximately a 1% average absolute prediction error when modeling processors experiencing both Markovian and non-Markovian stochastic Pauli errors. …”
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Characterization of Neural Interaction During Learning and Adaptation from Spike-Train Data by Liqiang Zhu, Ying-Cheng Lai, Frank C. Hoppensteadt, Jiping He

“…Our computation and analysis indicated that theadaptation tends to alter the connection topology of theunderlying neural network, yet the average interaction strength inthe network is approximately conserved before and after theadaptation. …”
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Improved estimates for extinction probabilities and times to extinction for populations of tsetse (Glossina spp) by Damian, Kajunguri, Elisha B., Are, John W., Hargrove

“…A published study used a stochastic branching process to derive equations for the mean and variance of the probability of, and time to, extinction in population of tsetse flies (Glossina spp) as a function of adult and pupal mortality, and the probabilities that a female is inseminated by a fertile male. …”
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Intelligent back-propagated neural networks to study nonlinear heat transfer in tangent-hyperbolic fluids by Muhammad Asif Zahoor Raja, Huma Tayyab, Aamna Muskan Malik, Qazi Mahmood Ul Hassan, Kottakkaran Sooppy Nisar, Muhammad Shoaib

“…The absolute error for each scenario of model instance is approximately 10−06, 10−05, 10−07, 10−05, and 10−08. …”
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Hybrid Prophet-NAR Model for Short-Term Electricity Load Forecasting by Winita Sulandari, Yudho Yudhanto, Etik Zukhronah, Isnandar Slamet, Hilman Ferdinandus Pardede, Paulo Canas Rodrigues, Muhammad Hisyam Lee

“…Specifically, it reduced Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) by approximately 21%-86% compared to the standalone Prophet model. …”
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Eco-reliable operation based on clean environmental condition for the grid-connected renewable energy hubs with heat pump and hydrogen, thermal and compressed air storage systems by Aboulbaba Eladeb, Ali Basem, Aman Sharma, Aashim Dhawan, Prabhat Sharma, Mohamed Bouzidi, Lioua Kolsi, Elnaz Naderi Drehshori

“…The incorporation of renewable hubs, equipped with storage units and heat pumps, has led to improvements in the economic, operational, reliability, and environmental conditions by approximately 44.1%, 28–90%, 85.6%, and 72.1% respectively, in comparison to load distribution studies.…”
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Dual Jet Interaction, Magnetically Arrested Flows, and Flares in Accreting Binary Black Holes by Sean M. Ressler, Luciano Combi, Bart Ripperda, Elias R. Most

“…With the aid of three-dimensional general-relativistic magnetohydrodynamic simulations that utilize an approximate, semianalytic, superimposed spacetime metric, we identify two such signatures for merging binaries. …”
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ESTIMATING COST CONTINGENCY FOR CONSTRUCTION PROJECTS: THE CHALLENGE OF SYSTEMIC AND PROJECT SPECIFIC RISK by J.I.T Buertey, Emmanuel Abeere-Inga, Theophilus Adjei Kumi

“…Data analysis using FMEA as a qualitative risk tool and univariate statistical analysis as a quantitative risk tool revealed that systemic risk accounted for approximately 64% of the cost drivers related of the construction cost uncertainty whilst projects specific risk accounted for 36% of the risk impact. …”
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Randomized radial basis function neural network for solving multiscale elliptic equations by Yuhang Wu, Ziyuan Liu, Wenjun Sun, Xu Qian

“…Subsequently, a selection of collocation points is stochastically sampled at the boundaries of the subdomain, ensuring the satisfaction of C ^0 and C ^1 continuity and boundary conditions to couple these localized solutions. …”
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