Search Results - "Chan Kheong Sann"
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A perspective on deep neural network-based detection for multilayer magnetic recording
Published in Applied physics letters (05-07-2021)“…This paper describes challenges, solutions, and prospects for data recovery in multilayer magnetic recording (MLMR)—the vertical stacking of magnetic media…”
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TDMR Platform Simulations and Experiments
Published in IEEE transactions on magnetics (01-10-2009)“…Two-dimensional magnetic recording (TDMR) is a novel architecture for magnetic recording systems proposed to achieve densities towards 10 Tb/in 2 . TDMR…”
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3
EXIT-Chart-Based LDPC Code Design for 2D ISI Channels
Published in IEEE transactions on magnetics (01-06-2013)“…In this paper, optimization of low-density parity-check (LDPC) codes to approach the symmetric information rate (SIR) of two-dimensional (2-D) intersymbol…”
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Journal Article Conference Proceeding -
4
Mechanisms of Minimum Skew Angle Actuation for Hard Disk Drives
Published in MATEC Web of Conferences (2016)“…The utilization of voice coil motor (VCM) rotary actuator in hard disk drives (HDDs) results in skew angles between the read/write head and disk rotation…”
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Journal Article Conference Proceeding -
5
Optimization of the 3-D-MAMR Media Stack
Published in IEEE transactions on magnetics (01-09-2019)“…Microwave-assisted magnetic recording (MAMR) is an advanced magnetic recording scheme that is expected to extend the areal density beyond that achieved by…”
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Automated 2-D Scanning Setup on Spinstand for Evaluation of Ultra-High-Density Recording Data
Published in IEEE transactions on magnetics (01-11-2009)“…In this paper, we present an automated technique of extracting the two-dimensional (2-D) readback waveforms from the spinstand for evaluation of the written…”
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Journal Article Conference Proceeding -
7
Maximum Likelihood Detection for 3-D-MAMR
Published in IEEE transactions on magnetics (01-12-2019)“…3-D magnetic recording is a candidate next-generation magnetic recording where multiple recording layers are used, each layer storing its own independent data,…”
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Areal Density Capability of Dual-Structure Media for Microwave-Assisted Magnetic Recording
Published in IEEE transactions on magnetics (01-12-2019)“…In this article, we investigate the areal density capability (ADC) of dual-structure media for microwave-assisted magnetic recording. The recording medium…”
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9
Convolutional Neural Network-Based Media Noise Prediction and Equalization for TDMR Turbo-Detection With Write/Read TMR
Published in IEEE transactions on magnetics (01-03-2023)“…This article considers a turbo-detection system that includes a convolutional neural network (CNN)-based equalizer, a Bahl-Cocke-Jelinek-Raviv (BCJR) trellis…”
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10
Optimization of Dual-Structure Recording Media for Microwave-Assisted Magnetic Recording
Published in IEEE transactions on magnetics (01-07-2019)“…Selective recording on multiple structures may be possible with microwave-assisted magnetic recording. The number of parameters in even a dual-structure system…”
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Data Recovery for Multilayer Magnetic Recording
Published in IEEE transactions on magnetics (01-12-2019)“…Multilayer magnetic recording (MLMR) is a next-generation technology that has the potential to enhance the longevity of magnetic recording technology by…”
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12
Deep Neural Network a Posteriori Probability Detector for Two-Dimensional Magnetic Recording
Published in IEEE transactions on magnetics (01-06-2020)“…In two-dimensional magnetic recording (TDMR) channels, intersymbol interference (within and between tracks) and pattern-dependent media noise are impediments…”
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13
A Study on Block-Based Neural Network Equalization in TDMR System With LDPC Coding
Published in IEEE transactions on magnetics (01-11-2019)“…To achieve a high track density, two-dimensional magnetic recording (TDMR) is combined with shingled magnetic recording (SMR). SMR makes it possible to record…”
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14
Analysis of the Joint Viterbi Detector/Decoder (JVDD) Over a Coded AWGN/ISI System ss an LDPC Alternative
Published in IEEE transactions on broadcasting (01-03-2019)“…The joint Viterbi detector/decoder (JVDD) has been proposed as an alternative to the powerful and ubiquitous low-density parity check (LDPC) coding schemes,…”
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15
Development of a MATLAB‐based graphical user interface to illustrate Coulomb's law and Gauss's law
Published in Computer applications in engineering education (01-09-2024)“…Coulomb's law and Gauss's law are two fundamental laws in electrostatics that involve electric charges and electric fields. These concepts that are not visible…”
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Deep Neural Network Media Noise Predictor Turbo-Detection System for 1-D and 2-D High-Density Magnetic Recording
Published in IEEE transactions on magnetics (01-03-2021)“…This article presents a concatenated Bahl-Cocke-Jelinek-Raviv (BCJR) detector, low-density parity-check (LDPC) decoder, and deep neural network (DNN)…”
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Deep Neural Network-Based Detection and Partial Response Equalization for Multilayer Magnetic Recording
Published in IEEE transactions on magnetics (01-03-2021)“…To increase the storage capacity limit of magnetic recording channels, recent studies proposed multilayer magnetic recording (MLMR): the vertical stacking of…”
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Convolutional Neural Network Based Symbol Detector for Two-Dimensional Magnetic Recording
Published in IEEE transactions on magnetics (01-03-2021)“…Data detection in magnetic recording (MR) channels can be viewed as an image processing problem, proceeding from the 2-D image of readback bits, to higher…”
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19
Analysis of the frequency-domain block LMS algorithm
Published in IEEE transactions on signal processing (01-08-2000)“…We present a new analysis of the frequency-domain block least-mean-square (FBLMS) algorithm. An earlier analysis uses a mapping of the frequency-domain…”
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Turbo-Detection for Multilayer Magnetic Recording Using Deep Neural Network-Based Equalizer and Media Noise Predictor
Published in IEEE transactions on magnetics (01-04-2022)“…This article considers deep neural network (DNN)-based turbo-detection for multilayer magnetic recording (MLMR), an emerging hard disk drive (HDD) technology…”
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