Yao Qinghua, Qiu Benhua
Xuchang Vocational College of Ceramic, Xuchang, Henan, China.
Department of Basic Courses, Zhengzhou University of Science and Technology, Zhengzhou, Henan, China.
PeerJ Comput Sci. 2024 Feb 27;10:e1873. doi: 10.7717/peerj-cs.1873. eCollection 2024.
To improve the processing effect of computer random signals, the manuscript employs the intelligent signal recognition algorithm to design a combinatorial mathematical model for computer random signals, and studies the parameter estimation of conventional frequency hopping signal (FHS) based on optimizing kernel function (KF). First, the mathematical form and graphical representation of the ambiguity function of the conventional FHS are explored. Furthermore, a new KF is presented according to its fuzzy function (FF) and the parameters of conventional FHSs are estimated according to the time-frequency distribution corresponding to the KF. Then, simulation experiments are carried out in different types of interference noise environments. The proposed combinatorial mathematical model for computer random signals shows a practical impact, and can effectively improve the effect of random signal combination.
为提高计算机随机信号的处理效果,本文采用智能信号识别算法设计计算机随机信号的组合数学模型,并基于优化核函数(KF)研究常规跳频信号(FHS)的参数估计。首先,探究了常规FHS模糊函数的数学形式和图形表示。此外,根据其模糊函数(FF)提出了一种新的KF,并根据与该KF对应的时频分布估计常规FHS的参数。然后,在不同类型的干扰噪声环境中进行了仿真实验。所提出的计算机随机信号组合数学模型具有实际影响,能够有效提高随机信号组合的效果。