Multiple description (MD) coding is a source coding technique for information transmission over unreliable networks. In MD coding, the coder generates several different descriptions of the same signal and the decoder can produce a useful reconstruction of the source with any received subset of these descriptions. In this paper, we study the problem of MD coding of stationary Gaussian sources with memory. First, we compute an approximate MD rate distortion region for these sources, which we prove to be asymptotically tight at high rates. This region generalizes the MD rate distortion region of El Gamal and Cover (1982), and Ozarow (1980) for memoryless Gaussian sources. Then, we develop an algorithm for the design of optimal two-channel biorthogonal filter banks for MD coding of Gaussian sources. We show that optimal filters are obtained by allocating the redundancy over frequency with a reverse "water-filling" strategy. Finally, we present experimental results which show the effectiveness of our filter banks in the low complexity, low rate regime
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机译：多描述（MD）编码是一种用于在不可靠网络上进行信息传输的源编码技术。在MD编码中，编码器会生成同一信号的多个不同描述，并且解码器可以使用这些描述的任何接收子集对源进行有用的重构。在本文中，我们研究具有记忆的固定高斯源的MD编码问题。首先，我们为这些源计算一个近似的MD率失真区域，我们证明了它在高速率下渐近紧。该区域概括了El Gamal and Cover（1982）和Ozarow（1980）对于无记忆高斯源的MD率失真区域。然后，我们开发了一种算法，用于设计用于高斯源MD编码的最佳两通道双正交滤波器组。我们显示出最佳滤波器是通过使用反向“注水”策略在整个频率上分配冗余来获得的。最后，我们提供了实验结果，这些结果表明了我们的滤波器组在低复杂度，低费率条件下的有效性
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