An important class of universal encoders is the one where theencoder is fed with two inputs: a) the incoming string of data to becompressed, b) a “training sequence” that consists of thelast N data symbols that have been processed (i.e. a sliding windowalgorithm). We consider fixed-to-variable universal encoders thatnoiselessly compress blocks of some fixed length and derive universalbounds on the rate of approach of the compression to the l-th order (perletter) entropy H(X1l) or to the smallerconditional entropy H(X1l-k|X0-k+1) as a function of l and of the length N of the training sequenceX0-N+1展开▼
机译：通用编码器的重要一类是
编码器有两个输入：a）要输入的数据字符串
b）由以下部分组成的“训练序列”：
最后N个已处理的数据符号（即滑动窗口）
算法）。我们考虑固定到变量的通用编码器
无噪声地压缩某些固定长度的块并获得通用
压缩到l阶的逼近率的界限（每
字母）熵H（X 1 l ）或更小
条件熵H（X 1 l-k | X 0 -k + 1
）作为l和训练序列长度N的函数
X 0 -N + 1
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