Trapping-set database for a low-density parity-check decoder


A machine-implemented method of generating trapping-set information for use in LDPC-decoding processing of read signals generated, e.g., by sensing a storage medium, such as a magnetic platter. In one embodiment, the method can be implemented as an add-on to any other trapping-set search method in which the discovered trapping sets are evaluated to determine their influence on the overall bit-error rate and/or error-floor characteristics of the LDPC decoder. The method can advantageously reuse at least some of the computational results obtained during this evaluation, thereby requiring a relatively small amount of additional computations, while providing a significant benefit of discovering many more trapping sets in addition to the ones that are being evaluated.

Aleksandr Petiushko Александр Петюшко
Aleksandr Petiushko Александр Петюшко
Director, Head of ML Research / Adjunct Professor / PhD

Principal R&D Researcher (15+ years of experience), R&D Technical Leader (10+ years of experience), and R&D Manager (8+ years of experience). Running and managing industrial research and academic collaboration (35+ publications, 30+ patents). Hiring and transforming AI/ML teams. Inspired by theoretical computer science and how it changes the world.