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Channel modeling, signal processing ...

University of California, San Diego., Electrical Engineering (Communication Theory and Systems).

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Channel modeling, signal processing and coding for perpendicular magnetic recording.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Channel modeling, signal processing and coding for perpendicular magnetic recording./
作者:	Wu, Zheng.
面頁冊數:	137 p.
附註:	Advisers: Jack K. Wolf; Paul H. Siegel.
Contained By:	Dissertation Abstracts International69-12B.
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3339060
ISBN:	9780549945161

Channel modeling, signal processing and coding for perpendicular magnetic recording.
Wu, Zheng.

Channel modeling, signal processing and coding for perpendicular magnetic recording. - 137 p.

Advisers: Jack K. Wolf; Paul H. Siegel.

Thesis (Ph.D.)--University of California, San Diego, 2009.

With the increasing areal density in magnetic recording systems, perpendicular recording has replaced longitudinal recording to overcome the superparamagnetic limit. Studies on perpendicular recording channels including aspects of channel modeling, signal processing and coding techniques are presented in this dissertation.

ISBN: 9780549945161Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Channel modeling, signal processing and coding for perpendicular magnetic recording.
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100 1 $a Wu, Zheng. $3 1064955
245 1 0 $a Channel modeling, signal processing and coding for perpendicular magnetic recording.
300 $a 137 p.
500 $a Advisers: Jack K. Wolf; Paul H. Siegel.
500 $a Source: Dissertation Abstracts International, Volume: 69-12, Section: B, page: 7723.
502 $a Thesis (Ph.D.)--University of California, San Diego, 2009.
520 $a With the increasing areal density in magnetic recording systems, perpendicular recording has replaced longitudinal recording to overcome the superparamagnetic limit. Studies on perpendicular recording channels including aspects of channel modeling, signal processing and coding techniques are presented in this dissertation.
520 $a To optimize a high density perpendicular magnetic recording system, one needs to know the tradeoffs between various components of the system including the read/write transducers, the magnetic medium, and the read channel. We extend the work by Chaichanavong on the parameter optimization for systems via design curves. Different signal processing and coding techniques are studied. Information-theoretic tools are utilized to determine the acceptable region for the channel parameters when optimal detection and linear coding techniques are used. Our results show that a considerable gain can be achieved by the optimal detection and coding techniques.
520 $a The read-write process in perpendicular magnetic recording channels includes a number of nonlinear effects. Nonlinear transition shift (NLTS) is one of them. The signal distortion induced by NLTS can be reduced by write precompensation during data recording. We numerically evaluate the effect of NLTS on the read-back signal and examine the effectiveness of several write precompensation schemes in combating NLTS in a channel characterized by both transition jitter noise and additive white Gaussian electronics noise. We also present an analytical method to estimate the bit-error-rate and use it to help determine the optimal write precompensation values in multi-level precompensation schemes.
520 $a We propose a mean-adjusted pattern-dependent noise predictive (PDNP) detection algorithm for use on the channel with NLTS. We show that this detector can offer significant improvements in bit-error-rate (BER) compared to conventional Viterbi and PDNP detectors. Moreover, the system performance can be further improved by combining the new detector with a simple write precompensation scheme.
520 $a Soft-decision decoding for algebraic codes can improve performance for magnetic recording systems. In this dissertation, we propose two soft-decision decoding methods for tensor-product parity codes. We also present a list decoding algorithm for generalized error locating codes.
590 $a School code: 0033.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Physics, Electricity and Magnetism. $3 1019535
690 $a 0544
690 $a 0607
710 2 $a University of California, San Diego. $b Electrical Engineering (Communication Theory and Systems). $3 1018760
773 0 $t Dissertation Abstracts International $g 69-12B.
790 $a 0033
790 1 0 $a Lomakin, Vitaliy $e committee member
790 1 0 $a Siegel, Paul H., $e advisor
790 1 0 $a Small, Lance W. $e committee member
790 1 0 $a Vardy, Alexander $e committee member
790 1 0 $a Wolf, Jack K., $e advisor
791 $a Ph.D.
792 $a 2009
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3339060