Conditional Entropies of k-Deletion/Insertion Channels

التفاصيل البيبلوغرافية
العنوان: Conditional Entropies of k-Deletion/Insertion Channels
المؤلفون: Singhvi, Shubhransh, Sabary, Omer, Bar-Lev, Daniella, Yaakobi, Eitan
سنة النشر: 2024
المجموعة: Computer Science
Mathematics
مصطلحات موضوعية: Computer Science - Information Theory
الوصف: The channel output entropy of a transmitted sequence is the entropy of the possible channel outputs and similarly the channel input entropy of a received sequence is the entropy of all possible transmitted sequences. The goal of this work is to study these entropy values for the k-deletion, k-insertion channels, where exactly k symbols are deleted, inserted in the transmitted sequence, respectively. If all possible sequences are transmitted with the same probability then studying the input and output entropies is equivalent. For both the 1-deletion and 1-insertion channels, it is proved that among all sequences with a fixed number of runs, the input entropy is minimized for sequences with a skewed distribution of their run lengths and it is maximized for sequences with a balanced distribution of their run lengths. Among our results, we establish a conjecture by Atashpendar et al. which claims that for the 1-deletion channel, the input entropy is maximized by the alternating sequences over all binary sequences. This conjecture is also verified for the 2-deletion channel, where it is proved that constant sequences with a single run minimize the input entropy.
Comment: arXiv admin note: substantial text overlap with arXiv:2202.03024
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2407.10026
رقم الأكسشن: edsarx.2407.10026
قاعدة البيانات: arXiv