论文标题
重建的不确定性，并从统一串联噪声中列出列表编码
Uncertainty of Reconstruction with List-Decoding from Uniform-Tandem-Duplication Noise
论文作者
论文摘要
我们在均匀串联噪声的背景下为重建代码提出了列表编码方案，可以将其视为关联内存模型在此设置中的应用。我们在渐近术语中发现与$ m> 2 $ strings（以前的论文被认为$ m = 2 $）相关的不确定性，其中代码字是从错误纠正的代码中获取的。因此，我们发现设计最小距离，错误数量，可接受的列表大小和结果不确定性之间的权衡，这对应于成功重建的所需的不同检索输出数量。因此，可以看出，通过接受列表来编码，可以减少编码冗余，或所需的读数数，或两者兼而有之。
We propose a list-decoding scheme for reconstruction codes in the context of uniform-tandem-duplication noise, which can be viewed as an application of the associative memory model to this setting. We find the uncertainty associated with $m>2$ strings (where a previous paper considered $m=2$) in asymptotic terms, where code-words are taken from an error-correcting code. Thus, we find the trade-off between the design minimum distance, the number of errors, the acceptable list size and the resulting uncertainty, which corresponds to the required number of distinct retrieved outputs for successful reconstruction. It is therefore seen that by accepting list-decoding one may decrease coding redundancy, or the required number of reads, or both.
