Introducing frequency agility into a distributed multipleinput multiple-output(MIMO)radar can significantly enhance its anti-jamming ability.However,it would cause the sidelobe pedestal problem in multi-target paramet...Introducing frequency agility into a distributed multipleinput multiple-output(MIMO)radar can significantly enhance its anti-jamming ability.However,it would cause the sidelobe pedestal problem in multi-target parameter estimation.Sparse recovery is an effective way to address this problem,but it cannot be directly utilized for multi-target parameter estimation in frequency-agile distributed MIMO radars due to spatial diversity.In this paper,we propose an algorithm for multi-target parameter estimation according to the signal model of frequency-agile distributed MIMO radars,by modifying the orthogonal matching pursuit(OMP)algorithm.The effectiveness of the proposed method is then verified by simulation results.展开更多
Transport risk management is one of the predominant issues to any industry for supplying their goods safely and in time to their beneficiaries. Damaging goods or delaying the shipping both make penalty to the company ...Transport risk management is one of the predominant issues to any industry for supplying their goods safely and in time to their beneficiaries. Damaging goods or delaying the shipping both make penalty to the company and also reduce the goodwill of the company. Every way of transportation routes has to be comfy which can make sure the supplies will attain without damaging goods and in time and additionally cost efficiently. In this paper, we find a few not unusual risks which might be concerned about all types of way of routes which include Highway, Waterway, Airway, Railway and so forth. Additionally, we proposed a technique to attain multiple optimal solutions by using Modified Distribution Method (MODI) of a transportation problem. Finally, we reduce the risks by minimizing the possible number of transportation routes using multi-optimality technique of the transportation problem.展开更多
The objective of this article is to provide a novel extension of the conventional inverse Weibull distribution that adds an extra shape parameter to increase its flexibility.This addition is beneficial in a variety of...The objective of this article is to provide a novel extension of the conventional inverse Weibull distribution that adds an extra shape parameter to increase its flexibility.This addition is beneficial in a variety of fields,including reliability,economics,engineering,biomedical science,biological research,environmental studies,and finance.For modeling real data,several expanded classes of distributions have been established.The modified alpha power transformed approach is used to implement the new model.The datamatches the new inverseWeibull distribution better than the inverse Weibull distribution and several other competing models.It appears to be a distribution designed to support decreasing or unimodal shaped distributions based on its parameters.Precise expressions for quantiles,moments,incomplete moments,moment generating function,characteristic generating function,and entropy expression are among the determined attributes of the new distribution.The point and interval estimates are studied using the maximum likelihood method.Simulation research is conducted to illustrate the correctness of the theoretical results.Three applications to medical and engineering data are utilized to illustrate the model’s flexibility.展开更多
文摘Introducing frequency agility into a distributed multipleinput multiple-output(MIMO)radar can significantly enhance its anti-jamming ability.However,it would cause the sidelobe pedestal problem in multi-target parameter estimation.Sparse recovery is an effective way to address this problem,but it cannot be directly utilized for multi-target parameter estimation in frequency-agile distributed MIMO radars due to spatial diversity.In this paper,we propose an algorithm for multi-target parameter estimation according to the signal model of frequency-agile distributed MIMO radars,by modifying the orthogonal matching pursuit(OMP)algorithm.The effectiveness of the proposed method is then verified by simulation results.
文摘Transport risk management is one of the predominant issues to any industry for supplying their goods safely and in time to their beneficiaries. Damaging goods or delaying the shipping both make penalty to the company and also reduce the goodwill of the company. Every way of transportation routes has to be comfy which can make sure the supplies will attain without damaging goods and in time and additionally cost efficiently. In this paper, we find a few not unusual risks which might be concerned about all types of way of routes which include Highway, Waterway, Airway, Railway and so forth. Additionally, we proposed a technique to attain multiple optimal solutions by using Modified Distribution Method (MODI) of a transportation problem. Finally, we reduce the risks by minimizing the possible number of transportation routes using multi-optimality technique of the transportation problem.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project No. (PNURSP2022R50),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The objective of this article is to provide a novel extension of the conventional inverse Weibull distribution that adds an extra shape parameter to increase its flexibility.This addition is beneficial in a variety of fields,including reliability,economics,engineering,biomedical science,biological research,environmental studies,and finance.For modeling real data,several expanded classes of distributions have been established.The modified alpha power transformed approach is used to implement the new model.The datamatches the new inverseWeibull distribution better than the inverse Weibull distribution and several other competing models.It appears to be a distribution designed to support decreasing or unimodal shaped distributions based on its parameters.Precise expressions for quantiles,moments,incomplete moments,moment generating function,characteristic generating function,and entropy expression are among the determined attributes of the new distribution.The point and interval estimates are studied using the maximum likelihood method.Simulation research is conducted to illustrate the correctness of the theoretical results.Three applications to medical and engineering data are utilized to illustrate the model’s flexibility.
