In IEEE 802.11 wireless LAN, as the number of nodes increases, collisions will increase correspondingly, channel utilization will decline, and the total throughput will decline instead of increasing, leading to system...
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In IEEE 802.11 wireless LAN, as the number of nodes increases, collisions will increase correspondingly, channel utilization will decline, and the total throughput will decline instead of increasing, leading to system performance degradation. Through in-depth analysis of the root cause of this problem, this paper designs a simple and effective algorithm, which uses ARMA filtering algorithm to measure the conditional collision probability and then calculate the number of nodes in the network. The AP tells all nodes in the network in the form of broadcast when the number of nodes in the network changes, after all nodes receive the broadcast sent by the AP, they dynamically adjust the network parameters accordingly. Finally, NS2 simulation software is used to conduct simulation experiments in a variety of network scenarios, and the experimental results verify that the algorithm in this paper is simple and effective, with less changes to IEEE 802.11, and is suitable for use and promotion in wireless networks. It can optimize the network system performance based on the number of nodes, improve the system throughput, and significantly improve the network performance. According to the number and density of nodes, the algorithm reduces the collision probability by dynamically adjusting the timeslot, accordingly increases the total network throughput, and achieves the purpose of effectively improving the network performance.
We present a theoretical study to examine the optical conductivity of an electron gas in the presence of a pulsed terahertz (THz) radiation field. Applying a very simple Drude like approach, we calculate the transit c...
We present a theoretical study to examine the optical conductivity of an electron gas in the presence of a pulsed terahertz (THz) radiation field. Applying a very simple Drude like approach, we calculate the transit current for an electron gas driven by a pulsed light field. By taking three types of the pulsed radiation fields with different analytical forms, we prove analytically or numerically that although the corresponding transit current depends on the shape of the radiation field in time-domain, the optical conductivity in frequency-domain is independent upon the profile of the pulsed light field when optical conductivity in frequency-domain is obtained by Fourier transformation of both the pulsed radiation field and the transit current. Thus, the optical conductivity in frequency-domain can be described by the well known Drude formula even in the presence of the pulsed THz field. This finding can be applied for experimental measurement of the real and imaginary parts of optical conductivity in electronic and optoelectronic materials by using, e.g., the THz time-domain spectroscopy (TDS).
Based on the IVS simulation platform, the system uses IOT technology to monitor and control the environmental data onto greenhouse orchards for the purpose of orchard wisdom management. The system realizes the bi-dire...
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Based on the IVS simulation platform, the system uses IOT technology to monitor and control the environmental data onto greenhouse orchards for the purpose of orchard wisdom management. The system realizes the bi-directional function of manual remote as well as intelligent self-control through integrated sensors and wireless communication network, and optimizes through fuzzy control algorithm, PID algorithm and supervised learning algorithm to achieve the monitoring of data such as air temperature and humidity, soil temperature and humidity and carbon dioxide concentration in the park, so that the environment is always maintained in the range suitable for fruit tree growth. Finally, a QR code is added to each batch of fruits to build a traceability function of food safety.
At present, the fast-changing functional requirements of simulation control system in Aerospace and navigation, where various hardware boards are used, have caused the high complexity and long development cycle of con...
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At present, the fast-changing functional requirements of simulation control system in Aerospace and navigation, where various hardware boards are used, have caused the high complexity and long development cycle of control systems. Although such systems have a certain degree of similarity, they are not well reused. In order to solve these problems, this paper puts forward the idea of using the software product line to model the control system of spacecraft and designs a framework. Using this framework, a simulation wave data acquisition software is developed. The application of this framework can achieve maximum granularity of software reuse, and improve the development efficiency.
The accurate prediction of power load is of great significance for the safe operation of the smart grid and the power transactions of market participants since the power load data series exhibits nonlinearity and vola...
The accurate prediction of power load is of great significance for the safe operation of the smart grid and the power transactions of market participants since the power load data series exhibits nonlinearity and volatility. In this paper, a new hybrid approach for deterministic short-term power load forecasting is proposed based on wavelet transform and deep deterministic policy gradient. In this approach, the original load data sequence is first decomposed by wavelet transform into some sub-frequency load sequences, and each sub-frequency can have better outlines and behavior. A deep deterministic policy gradient model is then employed to extract nonlinear features and invariant structures of each sub-frequency for power load. Finally, a new reward function for imbalanced samples is developed to effectively evaluate the policy score of the actor-network and further improve the prediction performance of the deep deterministic policy gradient. The proposed deterministic forecasting approach is used to actual power load data from an independent system operator from a city in China. The prediction results of the proposed method are presented in case studies, which have been demonstrated to achieve superior performance in terms of seasons and various prediction horizons compared with other prediction models.
Solving Lur'e equations plays a critical role in addressing linear-quadratic optimal control (LQOC) problems, especially in cases where the control cost matrices are singular. This paper introduces, for the first ...
Solving Lur'e equations plays a critical role in addressing linear-quadratic optimal control (LQOC) problems, especially in cases where the control cost matrices are singular. This paper introduces, for the first time, two novel zeroing neural network (ZNN) models—ZNNLE and ZNNLE-LQOC—specifically designed to solve the Lur'e equation system and the LQOC problem, respectively. The proposed models extend the applicability of the ZNN methodology to these challenging scenarios by offering robust and efficient solutions to time-varying matrix equations. Theoretical analyses confirm the validity of both models, while numerical simulations and practical applications demonstrate their effectiveness. Moreover, a comparative study with an enhanced alternating-direction implicit (ADI) method highlights the superior performance of the ZNNLE-LQOC model in solving LQOC problems.
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