{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/81364"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/81364","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Full-Surface Data Storage","abstract":"First, serial techniques are generalized to full-surface applications and the resulting systems analyzed for bit error rate (BER) performance under varying data density and noise levels. A multitrack Viterbi algorithm (MVA) performs well; however, the computational complexity limits the achievable data density. Equalization methods are introduced to increase achievable density. Iterative techniques based on greedy optimization are also studied. Though requiring relatively large computation, these iterative techniques have manageable memory requirements and can be used to implement soft-output algorithms. 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