Long-Short Term Memory-Based Application on Adaptive Cross-Platform Decoder for Bit Patterned Magnetic Recording

Chantakit, Teanchai; Buajong, Chaiwat; Warisarn, Chanon

doi:10.1109/access.2020.3018466

Cited by 7 publications

(2 citation statements)

References 41 publications

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“…e code reader sends the parsed data to the industrial computer through the serial port, and the software receives the data for analysis, processing, and correlation [14][15][16]. Interaction between humans and computers, between computers and software, and between humans and code readers all takes place on the display.…”

Section: The Composition Of the Electrical Systemmentioning

confidence: 99%

Fuzzy Application in the Design of QR Code Data Binding Based on the GD Packaging Machine

Wei

Chen

Haoran

2022

Mobile Information Systems

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The tracking of raw materials, production, and circulation links is carried out using QR codes in cigarette products. Each link’s current data collection and correlation analysis are still in the research and development stage. When used in conjunction with the GD packing machine’s production process feature, the QR code reader serves as an acquisition element for the process of data acquisition and the associated design for the tobacco packets and boxes, and the software is used to associate the received data and correct process exceptions. The system satisfies the design requirements, according to the results of the field verification.

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Section: The Composition Of the Electrical Systemmentioning

confidence: 99%

Fuzzy Application in the Design of QR Code Data Binding Based on the GD Packaging Machine

Wei

Chen

Haoran

2022

Mobile Information Systems

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“…The use of deep neural networks (DNNs) to solve the problems of magnetic recording systems was recently proposed [10]- [15]. Due to it was being composed of multiple non-linear modules, it enables learning very complex functions.…”

Section: Introductionmentioning

confidence: 99%

Track Misregistration Mitigation Using CNN-Based Method on Single-Reader/Two-Track Reading BPMR Systems

Kankhunthod

Warisarn

2023

IEEE Access

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One of the problems that cause a decrease in the performance of the ultra-high bit-patterned magnetic recording (BPMR) system is track misregistration (TMR). Since the gap between data tracks is extremely narrow, it easily affects keeping the reader in the desired position. Therefore, this paper proposes the track misregistration mitigation included the estimation and correction techniques on singlereader/two-track reading (SRTR) BPMR using only a readback signal. The TMR estimation technique uses the convolutional neural network (CNN) to estimate the TMR level by the histograms of the readback signal enabling minimization of the complexity of the CNN structure and amount of training time. The estimated TMR levels obtained from the proposed CNN-histogram-based method will then be utilized to detect the estimated recorded bit by the CNN-based data detector. The simulation shows that our proposed system provides better TMR prediction accuracy even though the system has to face higher media noise. Furthermore, the CNN-based data detectors perform superior to the partial response maximum likelihood (PRML) based data detector, especially in strong electronic noise situations and the severe imperfection of recording media.INDEX TERMS Bit-patterned magnetic recording (BPMR), convolutional neural network (CNN), supervised learning, track misregistration (TMR).

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Soft-information flipper based on long-short term memory networks for ultra-high density magnetic recording

2021

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Currently, researchers have been developing new ultra-high density magnetic recording technologies to meet the exponential growth of data storage demand. One of the main prospective technologies is bit-patterned media recording (BPMR) technology which is expected to upgrade the areal density (AD) up to 4.0 Terabit per square inch (Tb/in2). To achieve the expected high AD, the distance between each magnetic island in BPMR medium must; however, be reduced significantly, and it will enhance the two-dimensional (2-D) interference, namely inter-symbol interference (ISI) and inter-track interference (ITI). These two effects need to be probably handled to maintain overall system performance. Therefore, we propose a soft-information flipper based on long-short term memory (LSTM) networks combined with the rate-5/6 2-D modulation code in the coded three-track/three-head BPMR systems. In the proposed system, three soft-information sequences produced by the multiple 2-D soft-output Viterbi algorithms are employed as LSTM network inputs to generate the coded data sequences. During the supervised learning process, the known values of the coded data sequences are used as the targets at the output stage of LSTM network. The simulation results indicate that, at the same user density of 2.5 Tb/in2, the proposed system can provide bit-error-rate performance over both the soft-information flipping scheme based on a priori log-likelihood ratios summation and conventional uncoded systems. Moreover, the results also reveal that the proposed system is more robust to the media noise compared to other systems.

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Long-Short Term Memory-Based Application on Adaptive Cross-Platform Decoder for Bit Patterned Magnetic Recording

Cited by 7 publications

References 41 publications

Fuzzy Application in the Design of QR Code Data Binding Based on the GD Packaging Machine

Fuzzy Application in the Design of QR Code Data Binding Based on the GD Packaging Machine

Track Misregistration Mitigation Using CNN-Based Method on Single-Reader/Two-Track Reading BPMR Systems

Soft-information flipper based on long-short term memory networks for ultra-high density magnetic recording

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