ЭКСПЕРИМЕНТАЛЬНАЯ ОЦЕНКА МНОЖЕСТВА НЕПРОИЗВОДИТЕЛЬНЫХ ПЕРЕСТАНОВОК В ПРОЦЕДУРЕ ПОИСКА ЭКВИВАЛЕНТНЫХ КОДОВ

Abstract

The article proposes an algorithm to search for a complete set of unproductive permutations (UP) of code vector symbols to obtain a complete cognitive decoder map (CCDM) based on a PYTHON software product by example of the Bose-ChaudhuriHocquenghem (BCH) code (15, 7, 5). Data processing in control systems based on permutation decoding (PD) of binary codes is associated with a certain probability of obtaining UP symbols of accepted code vectors that do not allow obtaining an equivalent code (EC) due to the degeneracy of generating matrices corresponding to such permutations [1-5]. Attempts to estimate this parameter using the regularities of making error-correcting codes have led to results that are approximate in nature [6, 7]. To create a CCDM, it is important to know the exact result. Otherwise, the operation of the PD system becomes inadequate, since the decoder is to maintain two contradictory operating modes during its operation. On the one hand, a fast mode based on a cognitive map, including an incomplete list of UP, and, on the other hand, a training mode, which in the case of generated permutation not included in the map, significantly delays the processing of operational information due to the required time interval for assessing the degeneracy of the rearranged generating matrix of the probable EC.