{"paper":{"title":"Algorithm/Architecture Co-design of Proportionate-type LMS Adaptive Filters for Sparse System Identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.OH","authors_text":"Anindya Sundar Dhar, Subrahmanyam Mula, Vinay Chakravarthi Gogineni","submitted_at":"2017-03-17T09:12:11Z","abstract_excerpt":"This paper investigates the problem of implementing proportionate-type LMS family of algorithms in hardware for sparse adaptive filtering applications especially the network echo cancelation. We derive a re-formulated proportionate type algorithm through algorithm-architecture co-design methodology that can be pipelined and has an efficient architecture for hardware implementation. We study the convergence, steady-state and tracking performances of these re-formulated algorithms for white, color and speech inputs before implementing them in hardware. To the best of our knowledge this is the fi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.10658","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}