在有色高斯噪聲中離散時間檢測和估計的性能分析
THE PERFORMANCE ANALYSIS OF DISCRETE-TIME DETECTION AND ESTIMATION IN COLOUR GAUSSIAN NOISE
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摘要: 本文研究了在確定的觀察時間內(nèi),在有色高斯噪聲中離散時間檢測和估計的性能與樣本數(shù)之間的關(guān)系。指出相鄰樣本之間相關(guān)系數(shù)在0.10.2范圍內(nèi),廣義信噪比就能相當(dāng)接近極限值S2(T)。在討論二階相關(guān)噪聲時指出,由二階微分方程描寫的高斯過程的樣本序列一般不是AR(2)模型,但是當(dāng)樣本間隔△0時,卻可用AR(2)模型近似描寫序列,因此求極限信噪比時,可以較簡便地采用AR(2)模型。最后指出最大似然估計與似然比檢驗之間和兩者的性能測度之間的聯(lián)系。
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關(guān)鍵詞:
Abstract: The relation between the sample number and the performances of signal detection and paramater estimation in correlative Gaussian noise in fixed time T is investigated. It is pointed out that when the autocorrelation coefficient between the neighbour samples in the range of 0.1-0.2, the general SNR S2[T(XL)] will approach to the limit of SNR S2(T). It is also pointed out that the sample sequences of the solution of a second order differential equation generally is not an AR(2) model. But when the sample interval △0, the sample sequences can be described by AR(2). Therefore, S2(T) can be easily calculated. Finally, the relation between likelihood ratio detection and the maximum likelihood estimation is discussed. -
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