Bounding the compression loss of the FGK algorithm

R. Milidiú, E. Laber, A. Pessoa
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引用次数: 13

Abstract

[Summary form only given]. For data communication purposes, the initial parsing required by the static Huffman algorithm represents a big disadvantage. This is because the data must be transmitted on-line. As soon as the symbol arrives at the transmitter, it must be encoded and transmitted to the receiver. In these situations, adaptive Huffman codes have been largely used. This method determines the mapping from symbol alphabet to codewords based upon a running estimate of the alphabet symbol weights. The code is adaptive, just changing to remain optimal for the current estimates. Two methods have been presented in the literature for implementing dynamic Huffman coding. The first one was the FGK algorithm (Knuth, 1985) and the second was the /spl Lambda/ algorithm (Vitter, 1987). Vitter proved that the total number of bits D/sub t/ transmitted by the FGK algorithm for a message with t symbols is bounded below by S/sub t/-n+1, where S/sub t/ is the number of bits required by the static Huffman method and bounded above by 2S/sub t/+t-4n+2. Furthermore, he conjectured that D/sub t/ is bounded above by S/sub t/+O(t). We present an amortized analysis to prove this conjecture by showing that D/sub t//spl les/S/sub t/+2t-2k-[log min(k+1,n)], where k is the number of distinct symbols in the message. We also present an example where D/sub t/=S/sub t/+2t-2k-3[(t-k)/k]-[log(k+1)], showing that the proposed bound is asymptotically tight. These results explain the good performance of FGK observed by some authors through practical experiments.
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限制FGK算法的压缩损失
[仅提供摘要形式]。对于数据通信的目的,静态霍夫曼算法所需的初始解析是一个很大的缺点。这是因为数据必须在线传输。符号一到达发射机,就必须进行编码并传送给接收机。在这些情况下,自适应霍夫曼码被大量使用。该方法根据对字母符号权重的运行估计来确定从符号字母表到码字的映射。代码是自适应的,只是更改以保持当前估计的最佳状态。文献中提出了两种实现动态霍夫曼编码的方法。第一个是FGK算法(Knuth, 1985),第二个是/spl Lambda/算法(Vitter, 1987)。Vitter证明了FGK算法对包含t个符号的消息传输的总比特数D/下标t/在下面以S/下标t/-n+1为界,其中S/下标t/为静态霍夫曼方法所需的比特数,在上面以2S/下标t/+t-4n+2为界。更进一步,他推测D/ t/以S/ t/+O(t)为上界。我们通过证明D/下标t//spl等于/S/下标t/+2t-2k-[log min(k+1,n)]给出了一个平摊分析来证明这个猜想,其中k是消息中不同符号的数目。我们还给出了一个D/下标t/=S/下标t/+2t-2k-3[(t-k)/k]-[log(k+1)]的例子,证明了所提出的界是渐近紧的。这些结果解释了一些作者通过实际实验观察到的FGK的良好性能。
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