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Improved Upper Bounds to the Causal Quadratic Rate-Distortion Function for Gaussian Stationary Sources

机译:高斯平稳源的因果二次率失真函数的改进上限

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We improve the existing achievable rate regions for causal and for zero-delay source coding of stationary Gaussian sources under an average mean squared error distortion measure. To begin with, we find a closed-form expression for the information-theoretic causal rate-distortion function (RDF) under such distortion measure, denoted by Rcit(D), for first-order Gauss-Markov processes. Rcit(D) is a lower bound to the optimal performance theoretically attainable (OPTA) by any causal source code, namely Rcop(D). We show that, for Gaussian sources, the latter can also be upper bounded as Rcop(D) ≤ Rcit(D) + 0.5 log 2(2πe) bits/sample. In order to analyze Rcit(D) for arbitrary zero-mean Gaussian stationary sources, we introduce Rcit̅(D), the information-theoretic causal RDF when the reconstruction error is jointly stationary with the source. Based upon Rcit̅(D), we derive three closed-form upper bounds to the additive rate loss defined as Rcit̅(D) - R(D), where R(D) denotes Shannon''s RDF. Two of these bounds are strictly smaller than 0.5 bits/sample at all rates. These bounds differ from one another in their tightness and ease of evaluation; the tighter the bound, the more involved its evaluation. We then show that, for any source spectral density and any positive distortion D ≤ σx2, RU(D) can be realized by an additive white Gaussian noise channel surrounded by a unique set of causal pre-, post-, and feed- back niters. We show that finding such filters constitutes a convex optimization problem. In order to solve the latter, we propose an iterative optimization procedure that yields the optimal niters and is guaranteed to converge to Rcit̅(D). Finally, by esta- lishing a connection to feedback quantization, we design a causal and a zero-delay coding scheme which, for Gaussian sources, achieves an operational rate lower than Rcit̅(D) +0.254 and Rcit̅(D) + 0.754 bits/sample, respectively. This implies that the OPTA among all zero-delay source codes, denoted by Rzdop(D), is upper bounded as Rzdop(D) <; Rcit̅(D) + 1-254 <; R(D) + 1.754 bits/sample.
机译:我们改进了平均均方误差失真度量下的固定高斯源因果和零延迟源编码的现有可实现速率区域。首先,我们在这种失真量度下找到信息理论因果率失真函数(RDF)的闭式表达式,用R c it (D ),用于一阶高斯-马尔可夫过程。 R c it (D)是任何因果源代码,即R c <的理论上可达到的最佳性能(OPTA)的下限sup> op (D)。我们表明,对于高斯源,后者也可以作为R c op (D)≤R c it的上限(D)+ 0.5 log 2 (2πe)位/样本。为了分析任意零均值高斯平稳源的R c it (D),我们引入R c it̅(D),当重构误差与源共同静止时的信息理论因果RDF。根据R c it̅(D),我们得出加法速率损失的三个封闭形式上限,定义为R c it̅(D)-R(D),其中R(D)表示香农的RDF。在所有速率下,其中两个边界严格小于0.5位/样本。这些界限在紧密性和易于评估方面彼此不同。界限越紧密,其评估就越涉及。然后,我们表明,对于任何源光谱密度和任何正畸变D≤σ x 2 ,可以通过被加法器包围的加性高斯白噪声信道来实现RU(D)一组独特的因果关系,包括前,后和反馈。我们表明,找到这样的滤波器会构成凸优化问题。为了解决后者,我们提出了一个迭代优化程序,该程序产生最优的niters,并保证收敛到R c it̅(D)。最后,通过建立与反馈量化的联系,我们设计了一种因果和零延迟编码方案,对于高斯源,该方案可实现低于R c it̅(D)+0.254和R c it̅(D)分别为+ 0.754位/样本。这意味着在所有零延迟源代码中,用R zd op (D)表示的OPTA的上限为R zd < sup> op (D)<; R c it̅(D)+ 1-254 <; R(D)+ 1.754位/样本。

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