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    CHARACTER SEGMENTATION AND RECOGNITION ALGORITHM IN TEXT REGION IMAGE OF MANAGEMENT NUMBER

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    Maste

    System Identification Using Embedded Dynamic Signal Analyzer

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    ํ™€๋กœ๊ทธ๋žจ ์ €์žฅ์žฅ์น˜์—์„œ 2์ฐจ์› ์‹ฌ๋ณผ๊ฐ„ ๊ฐ„์„ญ ์ฑ„๋„ํ™˜๊ฒฝ์— ๊ฐ•์ธํ•œ ๋ณต์›์‹œ์Šคํ…œ์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    Doctor๋ณธ ๋…ผ๋ฌธ์€ ํ™€๋กœ๊ทธ๋žจ ์ €์žฅ์žฅ์น˜์—์„œ ๋ฐ์ดํ„ฐ ํŽ˜์ด์ง€์˜ ๋ณต์›์„ ์œ„ํ•œ ์„ธ ๊ฐ€์ง€์˜ ์ƒˆ๋กœ์šด ์‹œ์Šคํ…œ์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ๋ณต์›์‹œ์Šคํ…œ๋“ค์€ 2์ฐจ์› ์‹ฌ๋ณผ๊ฐ„ ๊ฐ„์„ญ ์ฑ„๋„ ํ™˜๊ฒฝ์— ๊ฐ•์ธํ•œ 2์ฐจ์› ๋ถ€๋ถ„์‘๋‹ต ์ตœ๋Œ€์œ ์‚ฌ(PRML) ์‹œ์Šคํ…œ๋“ค์ด๋‹ค. ๋ณธ ๋…ผ๋ฌธ์˜ ๊ถ๊ทน์ ์ธ ๋ชฉ์ ์€ ์‹ค์ œ ํ™€๋กœ๊ทธ๋žจ ์ €์žฅ์žฅ์น˜์˜ ๋ณต์› ์‹œ์Šคํ…œ์— ๋Œ€ํ•˜์—ฌ ๋น„ํŠธ์˜ค์œจ ์„ฑ๋Šฅ์„ ๊ฐœ์„ ํ•˜๋Š” ๊ฒƒ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ฒ˜๋ฆฌ ์‹œ๊ฐ„๊นŒ์ง€ ์ค„์ด๋Š” ๊ฒƒ์ด๋‹ค.์ฒซ ๋ฒˆ์งธ๋กœ, ๋ฐ์ดํ„ฐ ํŽ˜์ด์ง€์˜ ๋ณต์›์„ ์œ„ํ•œ ์ „ํ˜•์ ์ธ 2์ฐจ์› PRML ์‹œ์Šคํ…œ์€ ๋ถ€๋ถ„์‘๋‹ต(PR) ๋ถ€๋ถ„์—์„œ 2์ฐจ์› PR ํƒ€๊นƒ์„ ์‚ฌ์šฉํ•˜๊ธฐ ๋•Œ๋ฌธ์—, ์ตœ๋Œ€์œ ์‚ฌ(ML) ๋ถ€๋ถ„์˜ 2์ฐจ์› ๋ณตํ˜ธ๊ธฐ๋Š” ์šฐ์ˆ˜ํ•œ ๋น„ํŠธ์˜ค์œจ ์„ฑ๋Šฅ์„ ์œ„ํ•˜์—ฌ 2์ฐจ์› PR ํƒ€๊นƒ์— ์ •ํ™•ํžˆ ์ผ์น˜ํ•˜๋Š” ๊ฒฉ์ž๋„๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ์•ผ ํ•œ๋‹ค. ํ•˜์ง€๋งŒ ML ๋ถ€๋ถ„์—์„œ ๋‹จ์ง€ ํ•œ ๊ฐœ์˜ ๋น„ํ„ฐ๋น„ ๋ณตํ˜ธ๊ธฐ์— ๋Œ€ํ•œ ๊ฒฉ์ž๋„๋Š” ๋งค์šฐ ๋ณต์žกํ•˜๊ณ , ๋ณตํ˜ธํ™” ์‹œ ์ƒ๋‹นํ•œ ๊ณ„์‚ฐ ๋Ÿ‰์„ ํ•„์š”๋กœ ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋ฏ€๋กœ ๋ณธ ๋…ผ๋ฌธ์€ 2์ฐจ์› PR ํƒ€๊นƒ์— ๋Œ€ํ•œ ์ˆ˜์ •๋œ 2์ฐจ์› ์—ฐํŒ์ • ์ถœ๋ ฅ ๋น„ํ„ฐ๋น„ ์•Œ๊ณ ๋ฆฌ์ฆ˜(SOVA)์„ ์ด์šฉํ•œ 2์ฐจ์› PRML ์‹œ์Šคํ…œ์„ ์ œ์•ˆํ•œ๋‹ค. ๊ธฐ์กด ๋‘๊ฐœ์˜ 1์ฐจ์› PR ํƒ€๊นƒ์— ๋Œ€ํ•œ ์ˆ˜์ •๋œ 2์ฐจ์› SOVA๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ, ๋ณธ ๋…ผ๋ฌธ์˜ ์ˆ˜์ •๋œ 2์ฐจ์› SOVA๋Š” ์ˆ˜ํ‰, ์ˆ˜์ง ๋ฐฉํ–ฅ์— ๋Œ€ํ•œ 4๊ฐœ์˜ 1์ฐจ์› SOVA๋“ค๋กœ ๊ตฌ์„ฑ๋˜๊ณ , ์ฒซ ๋ฒˆ์งธ 1์ฐจ์› ์ˆ˜ํ‰ SOVA๋ฅผ ์ œ์™ธํ•œ ๋‚˜๋จธ์ง€ 1์ฐจ์› SOVA๋“ค์€ 2์ฐจ์› PR ํƒ€๊นƒ์— ๊ตฌ์กฐ์ ์œผ๋กœ ์ผ์น˜ํ•˜๋Š” ์ˆ˜์ •๋œ ๊ฒฉ์ž๋„๋ฅผ ์‚ฌ์šฉํ•œ๋‹ค. 2๊ฐœ์˜ 2์ฐจ์› ๋“ฑํ™”๊ธฐ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๊ธฐ์กด์˜ ์ˆ˜์ •๋œ 2์ฐจ์› SOVA์™€ ๋น„๊ตํ•˜์—ฌ, ์ œ์•ˆ๋œ ๋ณต์›์‹œ์Šคํ…œ์€ 2์ฐจ์› PR ํƒ€๊นƒ์— ๋Œ€ํ•˜์—ฌ ํ•œ ๊ฐœ์˜ 2์ฐจ์› ๋“ฑํ™”๊ธฐ๋ฅผ ์‚ฌ์šฉํ•จ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ํ–ฅ์ƒ๋œ ๋น„ํŠธ์˜ค์œจ ์„ฑ๋Šฅ์„ ๋‹ฌ์„ฑ ํ•  ์ˆ˜ ์žˆ๋‹ค.๋‘ ๋ฒˆ์งธ๋กœ, ์‹ค์ œ ํ™€๋กœ๊ทธ๋žจ ์ €์žฅ์žฅ์น˜์—์„œ ๋ฐ์ดํ„ฐ ํŽ˜์ด์ง€์— ๋Œ€ํ•œ ๋ณต์›์‹œ์Šคํ…œ์€ ๋น„ํŠธ์˜ค์œจ ์„ฑ๋Šฅ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ฒ˜๋ฆฌ์‹œ๊ฐ„ ์—ญ์‹œ ๊ณ ๋ คํ•˜์—ฌ์•ผ ํ•œ๋‹ค. ๋‘ ๊ฐ€์ง€ ์‚ฌํ•ญ ๋ชจ๋‘๋ฅผ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•˜์—ฌ, ๋ณธ ๋…ผ๋ฌธ์€ ๋Œ€๊ฐ ์š”์†Œ๋“ค์„ ํฌํ•จํ•œ 2์ฐจ์› PR ํƒ€๊นƒ, ๊ทธ 2์ฐจ์› PR ํƒ€๊นƒ์— ๋Œ€ํ•œ 2์ฐจ์› ๋“ฑํ™”๊ธฐ, ๊ฐ€๋ณ€์ ์ธ ์‹ ๋ขฐ์„ฑ ์ธ์ž๋ฅผ ์ด์šฉํ•œ 2์ฐจ์› SOVA๋กœ ๊ตฌ์„ฑ๋œ 2์ฐจ์› PRML ์‹œ์Šคํ…œ์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ๋ณต์›์‹œ์Šคํ…œ์—์„œ 2์ฐจ์› SOVA๋Š” ์ˆ˜ํ‰, ์ˆ˜์ง๋ฐฉํ–ฅ์— ๋Œ€ํ•œ 2๊ฐœ์˜ 1์ฐจ์› SOVA๋“ค์„ ์ด์šฉํ•˜์—ฌ ๋ณตํ˜ธํ™” ํ•œ๋‹ค. ๊ฐ๊ฐ์˜ 1์ฐจ์› SOVA๋Š” 2์ฐจ์› PR ํƒ€๊นƒ์— ๊ตฌ์กฐ์ ์œผ๋กœ ์ผ์น˜ํ•˜๋Š” ์ˆ˜์ •๋œ ๊ฒฉ์ž๋„๋ฅผ ์‚ฌ์šฉํ•˜๊ณ , ์ˆ˜์ •๋œ ๊ฒฉ์ž๋„๋Š” ๋ฐ์ดํ„ฐ ํŽ˜์ด์ง€์˜ ๋™๊ธฐํŒจํ„ด์—์„œ ๊ณ„์‚ฐ๋œ ๊ธฐ๋Œ€ ๊ฐ’์„ ์™ธ๋ถ€์ •๋ณด๋กœ ์‚ฌ์šฉํ•œ๋‹ค. ๋‘๊ฐœ์˜ 1์ฐจ์› SOVA๋“ค์— ๋Œ€ํ•œ ๋ณตํ˜ธํ™” ๊ฒฐ๊ณผ๋“ค๋กœ๋ถ€ํ„ฐ, 2์ฐจ์› SOVA๋Š” ๊ฐ€๋ณ€์ ์ธ ์‹ ๋ขฐ์„ฑ ์ธ์ž๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ฐ€์ค‘ ํ‰๊ท  ๊ฐ’์„ ์ถœ๋ ฅํ•œ๋‹ค. ๊ฐ€๋ณ€์ ์ธ ์‹ ๋ขฐ์„ฑ ์ธ์ž๋Š” ๊ฐ ๋ฐ์ดํ„ฐ ํŽ˜์ด์ง€๋งˆ๋‹ค ์ตœ์ ํ™” ๊ธฐ์ˆ ๊ณผ ์œ ์‚ฌํ•œ ๋ฐฉ๋ฒ•์œผ๋กœ ๊ฐฑ์‹ ๋œ๋‹ค. ์ œ์•ˆ๋œ ๋ณต์›์‹œ์Šคํ…œ์€ 4๊ฐœ์˜ 1์ฐจ์› SOVA๋“ค์„ ์‚ฌ์šฉํ•œ ๊ธฐ์กด์˜ ์ˆ˜์ •๋œ 2์ฐจ์› SOVA์™€ ๋น„๊ตํ•˜์—ฌ ๋น„ํŠธ์˜ค์œจ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ฌ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋‹จ์ง€ 2๊ฐœ์˜ 1์ฐจ์› SOVA๋“ค์„ ์‚ฌ์šฉํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๊ณ„์‚ฐ ๋Ÿ‰๋„ ์ค„์ผ ์ˆ˜ ์žˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๋ณธ ๋…ผ๋ฌธ์€ ์ž์ฒด์ฐธ์กฐ๋ฅผ ์ด์šฉํ•œ 2์ฐจ์› SOVA๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๋Š” 2์ฐจ์› PRML ์‹œ์Šคํ…œ์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ๋ณต์›์‹œ์Šคํ…œ์€ 2์ฐจ์› PR ํƒ€๊นƒ, 2์ฐจ์› ๋“ฑํ™”๊ธฐ, 2์ฐจ์› SOVA๋กœ ๊ตฌ์„ฑ๋˜๊ณ , 2์ฐจ์› SOVA๋Š” ๋‘ ๋ฒˆ์งธ ๋ณต์›์‹œ์Šคํ…œ๊ณผ ๋™์ผํ•˜๊ฒŒ ์ˆ˜ํ‰, ์ˆ˜์ง ๋ฐฉํ–ฅ์— ๋Œ€ํ•œ 2๊ฐœ์˜ 1์ฐจ์› SOVA๋“ค๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. 1์ฐจ์› SOVA์—์„œ 2์ฐจ์› PR ํƒ€๊นƒ์— ๊ตฌ์กฐ์ ์œผ๋กœ ์ •ํ™•ํ•˜๊ฒŒ ์ผ์น˜ํ•˜๋Š” ๊ฒฉ์ž๋„๋ฅผ ์กฐ์งํ•˜๊ธฐ ์œ„ํ•˜์—ฌ, ๋ณธ ๋…ผ๋ฌธ์€ 1์ฐจ์› SOVA์˜ ์™ธ๋ถ€์ •๋ณด์— ๋Œ€ํ•œ ์ž์ฒด์ฐธ์กฐ ๊ณผ์ •์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ๋ณต์›์‹œ์Šคํ…œ์€ 4๊ฐœ์˜ 1์ฐจ์› SOVA๋“ค์„ ์‚ฌ์šฉํ•œ ๊ธฐ์กด์˜ ์ˆ˜์ •๋œ 2์ฐจ์› SOVA์™€ ๋น„๊ตํ•˜์—ฌ ์ƒ๋Œ€์ ์œผ๋กœ ๋‚ฎ์€ ๊ณ„์‚ฐ๋Ÿ‰์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๋”์šฑ ์šฐ์ˆ˜ํ•œ ๋น„ํŠธ์˜ค์œจ ์„ฑ๋Šฅ์„ ๋‹ฌ์„ฑ ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋”๊ตฐ๋‹ค๋‚˜ ์ œ์•ˆ๋œ ๋ณต์›์‹œ์Šคํ…œ์€ ์•ž์„  ๋ณต์›์‹œ์Šคํ…œ๋“ค๊ณผ ๋‹ฌ๋ฆฌ 2๊ฐœ์˜ 1์ฐจ์› SOVA๋“ค์— ๋Œ€ํ•œ ๋ณ‘๋ ฌ ์ฒ˜๋ฆฌ๊ฐ€ ๊ฐ€๋Šฅํ•˜๋‹ค.This thesis proposes three new systems to reconstruct a data page for the holographic data storage (HDS). The proposed systems are robust two-dimensional (2D) partial response maximum likelihood (PRML) systems to channel circumstance with 2D inter-symbol interference (ISI). In this thesis, the final aim is not only to improve the bit error rate (BER) performance but also to reduce the processing time in a practical reconstruction system for the HDS.First, because a typical 2D PRML system to reconstruct the data page uses a 2D partial response (PR) target in the PR part, 2D decoder in the maximum likelihood (ML) part is required to use a trellis diagram in exact accordance with the 2D PR target for superior BER performancehowever, it is very complex and costly to organize only one Viterbi decoder in the ML part. Therefore, this thesis proposes a 2D PRML system using modified 2D soft-output Viterbi algorithm (SOVA) with 2D PR target. The modified 2D SOVA consists of four one-dimensional (1D) SOVAs (horizontal and vertical directions) that use a modified trellis diagram in structural accordance with the 2D PR target except for first horizontal 1D SOVA, based on the conventional modified 2D SOVA with two 1D PR targets. Despite using only one 2D equalizer for the 2D PR target, the proposed system can achieve the improved BER performance compared with the conventional modified 2D SOVA using two 2D equalizers.Second, a reconstruction system for the data page should account for the processing time as well as the BER performance in a practical HDS system. To improve both aspects, this thesis proposes a 2D PRML system composed of the 2D PR target including diagonal elements, 2D equalizer for the 2D PR target, and 2D SOVA with a variable reliability factor. The 2D SOVA performs two 1D SOVAs (horizontal and vertical directions) in structural accordance with the 2D PR target where extrinsic information uses the expected value calculated on a synchronization pattern of the data page. From the outputs of two 1D SOVAs, the 2D SOVA exports a weighted average using the reliability factor that is updated similarly as the optimization scheme for each page. The proposed system can achieve not only the improved BER performance but also the reduced computational complexity, because of using only two 1D SOVAs as compared with the conventional modified 2D SOVA having four 1D SOVAs.Finally, this thesis proposes a 2D PRML system using 2D SOVA with self reference for the data page. The proposed system consists of the 2D PR target, 2D equalizer, and 2D SOVA using just two 1D SOVAs in horizontal and vertical directions like second system. To accurately organize a trellis diagram of the 1D SOVA in structural accordance with the 2D PR target, this thesis proposes the self-reference process for the extrinsic information in the 1D SOVA. The proposed system can achieve BER performance superior to the conventional modified 2D SOVA having four 1D SOVAs despite the relatively low computational complexity. Moreover, parallel processing is possible in the two 1D SOVAs through the self-reference process unlike the former systems

    Modified 2D SOVA with 2D PR target for Holographic Data Storage

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    Design of U-turn Support System using EDS and 4WS

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