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.

翻译：我们提议在统一和重复噪音的背景下制定重建法规清单解码办法,可视为将联合记忆模型应用于这一环境,我们发现与m>2美元字符串(前一份文件认为为m=2美元)有关的不确定性,该字符串的编码词取自错误校正代码。因此,我们发现设计最低距离、误差数、可接受清单大小和由此产生的不确定性之间的取舍,这与成功重建所需的不同检索产出数相对应,因此,我们通过接受列表解码,可以减少编码冗余,或所需读数或两者的取舍。