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非高斯噪声模型参数的最大似然快速估计

Fast Maximum Likelihood Estimation of Class A Model
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摘要 研究了C1ass A统计物理模型,对该模型的参数估计提出了一种最大似然方法,利用FFT的优势降低运算量,通过对观测数据进行分类计算以保证精度要求,并设计了初始值估计方案.仿真实验表明,该方法精度高,迭代次数少,有较高的应用价值. This paper investigates the Class A noise model, and proposes a method to determine parameters of the model based on maximum likelihood estimation. The method uses FFT to reduce computation complexity and enhance performance by calculating two data groups from the original observed data. A method for estimating initial values is also proposed. Simulation results show that the method has good performance with a small number of iterations, and therefore is suitable for practical applications.
作者 蒋宇中 应文威 刘月亮
机构地区 海军工程大学电子工程学院
出处 《应用科学学报》 CAS CSCD 北大核心 2013年第2期165-169,共5页 Journal of Applied Sciences
基金 国防科工委资助项目
关键词 CLASS A噪声 非高斯噪声 最大似然估计 快速傅里叶变换 class A noise non-Gaussian noise maximum likelihood estimation fast Fourier transform （FFT）
分类号 TN822 [电子电信—信息与通信工程]
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参考文献10

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应用科学学报
2013年 第2期

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