摘要翻译:
在参数化框架下,研究了复杂带噪盲离散反卷积模型中反滤波器和电平噪声的一种新的估计方法。我们的估计方法是对Hankel形式特殊性质的充分利用的结果。还估计了输入信号的分布。建立了所有估计的强相合性和渐近分布。为了从经验上证明我们的估计程序的计算性能,增加了一致的模拟研究。
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英文标题:
《Parametric estimation in noisy blind deconvolution model: a new
estimation procedure》
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作者:
Emmanuelle Gautherat, Ghislaine Gayraud
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最新提交年份:
2007
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分类信息:
一级分类:Mathematics 数学
二级分类:Statistics Theory 统计理论
分类描述:Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计:例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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一级分类:Statistics 统计学
二级分类:Statistics Theory 统计理论
分类描述:stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近,贝叶斯推论,决策理论,估计,基础,推论,检验。
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英文摘要:
In a parametric framework, the paper is devoted to the study of a new estimation procedure for the inverse filter and the level noise in a complex noisy blind discrete deconvolution model. Our estimation method is a consequence of the sharp exploitation of the specifical properties of the Hankel forms. The distribution of the input signal is also estimated. The strong consistency and the asymptotic distribution of all estimates are established. A consistent simulation study is added in order to demonstrate empirically the computational performance of our estimation procedures.
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PDF链接:
https://arxiv.org/pdf/711.0587


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