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signal processing and Coding Techniques for 2-d Magnetic Recording: An Overview

PROCEEdINGS OF THE IEEE 2018年第2期106卷 286-318页

作者： Garani, Shayan Srinivasa dolecek, Lara Barry, John Sala, Frederic Vasic, Bane Indian Inst Sci Elect Syst Engn Dept Bengaluru 560012 India Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA Georgia Inst Technol Atlanta GA 30332 USA Univ Arizona Dept Elect & Comp Engn Tucson AZ 85721 USA

Two-dimensional magnetic recording (TdMR) is an emerging storage technology that aims to achieve areal densities on the order of 10 Tb/in 2, mainly driven by innovative channels engineering with minimal changes to existing head/ media designs within a systems framework. Significant additive areal density gains can be achieved by using TdMR over bit patterned media (BPM) and energy-assisted magnetic recording (EAMR). In TdMR, the sectors are inherently 2-d with reduced track pitch and bit widths, leading to severe 2-d intersymbol interference (ISI). This necessitates the development of powerful 2-d signal processing and coding algorithms for mitigating 2-d ISI, timing artifacts, jitter, and electronics noise resulting from irregular media grain positions and read-head electronics. The algorithms have to be eventually realized within a read/write channel architecture as a part of a system-on-chip (SoC) within the disk controller system. In this work, we provide a wide overview of TdMR technology, channel models and capacity, signal processing algorithms (detection and timing recovery), and error-correcting codes attuned to 2-d channels. The innovations and advances described not only make TdMR a promising future technology, but may serve a broader engineering audience as well.

关键词： 2-d intersymbol interference channels 2-d signal processing coding techniques magnetic storage read write channels systems architecture

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2-d adaptive autoregressive modeling using new lattice structure

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IEICE TRANSACTIONS ON FUNdAMENTALS OF ELECTRONICS COMMUNICATIONS ANd COMPUTER SCIENCES 1996年第8期E79A卷 1145-1150页

作者： Nakachi, T Yamashita, K Hamada, N Faculty of Science and Technology Keio University Yokohama-shi 223 Japan Faculty of Engineering University of the Ryukyus Okinawa-ken 903-01 Japan

The present paper investigates a two-dimensional (2-d) adaptive lattice filter used for modeling 2-d AR fields. The 2-d least mean square (LMS) lattice algorithm is used to update the filter coefficients. The proposed adaptive lattice filter can represent a wider class of 2-d AR fields than previous ones. Furthremore, its structure is also shown to possess orthogonality in the backward prediction error fields. These result in superior convergence and tracking properties to the adaptive transversal filter and other adaptive 2-d lattice models. Then, the convergence property of the proposed adaptive LMS lattice algorithm is discussed. The effectiveness of the proposed model is evaluated for parameter identification through computer simulation.

关键词： lattice filter 2-d signal processing adaptive filter linear prediction AR modeling

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New Efficient 2-d Lattice Structures for General Autoregressive Modeling of Random Fields

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IEEE TRANSACTIONS ON signal processing 2014年第6期62卷 1590-1602页

作者： Kayran, Ahmet Hamdi Camcioglu, Erdogan Istanbul Tech Univ Fac Elect & Elect Engn TR-34381 Istanbul Turkey

In this paper, we present a new efficient general 2-d autoregressive (AR) lattice modeling technique of random fields. Our proposed approach is capable of simultaneously providing all possible types of 2-d causal quarter-plane (QP) and asymmetric half-plane (ASHP) AR models for an arbitrary rectangular shape of the prediction support region (PSR). It is shown that it is also possible to obtain various noncausal half-plane AR models without any additional computational cost. This new lattice structure introduces only one row or one column of new observation points into the existing rectangular PSR when the order of the model increases in the horizontal or vertical direction at each of the recursive order incrementation stage, respectively. Starting with a given random data field, a set of auxiliary forward and backward prediction error fields (PEFs) for the horizontal and vertical directions are generated. After recursive order updates to the desired size of the rectangular PSR, all types of causal QP/ASHP and noncausal half-plane 2-d lattice models are obtained by deriving the appropriate PEF from the remaining ones. In addition to developing the basic theory, the presentation includes the derivation of the synthesis model transfer functions from the calculated lattice parameters. It is shown that the proposed auxiliary horizontal and vertical backward prediction error filters inherently generates the mutually orthogonal realization vectors and thus are optimum for all stages. The theory has been confirmed by computer simulations.

关键词： 2-d signal processing 2-d lattice filters linear prediction causal and noncausal modeling 2-d spectral estimation

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A COMPUTATIONALLY EFFICIENT TECHNIQUE FOR dERIVING 2-VARIABLE VSHP

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COMPUTERS & ELECTRICAL ENGINEERING 1995年第2期21卷 101-106页

作者： AHMAdI, M MAZINANI, A RAMACHANdRAN, V SRIdHAR, M CONCORDIA UNIV DEPT ELECT & COMP ENGNMONTREALPQ H3G 1M8CANADA

In this paper, a method is presented for the generation of 2-variable Very Strictly Hurwitz Polynomial (VSHP) free of any non-essential singularities of the second kind. The proposed technique utilizes the properties of the positive definite and semi-definite matrices along with resistive matrices to avoid calculation of higher order derivatives which are cumbersome.

关键词： 2-d FILTERS STABILITY OF 2-d SYSTEMS 2-d signal processing signal processing

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A 2-d adaptive joint-process lattice estimator for image restoration

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IEICE TRANSACTIONS ON FUNdAMENTALS OF ELECTRONICS COMMUNICATIONS ANd COMPUTER SCIENCES 1997年第1期E80A卷 140-147页

作者： Nakachi, T Yamashita, K Hamada, N Faculty of Science and Technology Keio University Yokohama-shi 223 Japan Faculty of Engineering University of the Ryukyus Okinawa-ken 903-01 Japan

The present paper examines a two-dimensional (2-d) joint-process lattice estimator and its implementation for image restoration. The gradient adaptive lattice (GAL) algorithm is used to update the filter coefficients. The proposed adaptive lattice estimator can represent a wider class of 2-d FIR systems than the conventional 2-d lattice models. Furthermore, its structure possesses orthogonality between the backward prediction errors. These results in superior convergence and tracking properties versus the transversal and other 2-d adaptive lattice estimators. The validity of the proposed model for image restoration is evaluated through computer simulations. In the examples, the implementation of the proposed lattice estimator as 2-d adaptive noise cancellator (ANC) and 2-d adaptive line enhancer (ALE) is considered.

关键词： lattice filter 2-d signal processing adaptive filter image processing

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An extended lattice model of two-dimensional autoregressive fields

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IEICE TRANSACTIONS ON FUNdAMENTALS OF ELECTRONICS COMMUNICATIONS ANd COMPUTER SCIENCES 1996年第11期E79A卷 1862-1869页

作者： Nakachi, T Yamashita, K Hamada, N Faculty of Science and Technology Keio University Yokohama-shi 223 Japan Faculty of Engineering University of the Ryukyus Okinawa-ken 903-01 Japan

We present an extended quarter-plane lattice model for generating two-dimensional (2-d) autoregressive fields. This work is a generalization of the extended lattice filter of diagonal form (ELdF) developed by Ertuzun et al. The proposed model represents a wider class of 2-d AR fields than conventional lattice models. Several examples are presented to demonstrate the applicability of the proposed model. Furthermore, the proposed structure is compared with other conventional lattice filters based on the computation of their entropy values.

关键词： lattice filter linear prediction AR modeling 2-d signal processing

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Two-dimensional least squares lattice algorithm for linear prediction

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IEICE TRANSACTIONS ON FUNdAMENTALS OF ELECTRONICS COMMUNICATIONS ANd COMPUTER SCIENCES 1997年第11期E80A卷 2325-2329页

作者： Nakachi, T Yamashita, K Hamada, N Faculty of Science and Technology Keio University Yokohama-shi 223 Japan

In this paper, we propose a two-dimensional (2-d) least-squares lattice (LSL) algorithm for the general case of the autoregressive (AR) model with an asymmetric half-plane (AHP) coefficient support. The resulting LSL algorithm gives both order and space recursions for the 2-d deterministic normal equations. The size and shape of the coefficient support region of the proposed lattice filter can be chosen arbitrarily Furthermore, the ordering of the support signal can be assigned arbitrarily. Finally, computer simulation for modeling a texture image is demonstrated to confirm the proposed model gives rapid convergence.

关键词： lattice filter 2-d signal processing adaptive filter texture analysis

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Fully Orthogonal 2-d Lattice Structures for Quarter-Plane and Asymmetric Half-Plane Autoregressive Modeling of Random Fields

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IEEE TRANSACTIONS ON signal processing 2019年第17期67卷 4507-4520页

作者： Kayran, Ahmet Hamdi Camcioglu, Erdogan Istanbul Tech Univ Fac Elect & Elect Engn TR-34469 Istanbul Turkey Istanbul Rumeli Univ Fac Comp Engn TR-34570 Silivri Turkey

This paper is mainly devoted to the derivation of a new fully orthogonal two-dimensional (2-d) lattice structure for general autoregressive (AR) modeling of random fields. Similar to the 1-d lattice theory, this approach is based on recursive incrementation of the prediction support region by adding a single past observation point at each stage. In addition to developing the basic theory, the presentation includes horizontal and vertical building blocks of the proposed causal 2-d AR lattice filters. The algorithm presented here is useful for high-resolution 2-d spectral analysis applications. It is shown that the new fully orthogonal 2-d lattice structure can he an efficient tool for high-resolution radar imaging.

关键词： 2-d signal processing 2-d lattice filters linear prediction autoregressive modeling 2-d spectral estimation

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Laser scanner versus CCd camera: a comparison

Industrial Metrology

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Industrial Metrology 1990年第2期1卷 155-164页

作者： Schmalfuß, Harald J. Erwin Sick GmbH 8000 München GB Surface Inspection Germany

A big challenge for automated industrial inspection systems is the hundred percentin-line surface inspection. Because of material speeds up to 10 m/s and material widths of several meters the amount of data received by the sensor systems is very large. In most cases the material flow is endless and therefore it is necessary that the complete inspection system works in real-time. Nearly 25 years ago the first systems based on laser scanning technology were introduced in industry. At the moment more than one thousand laser scanning systems are working worldwide. during the last five years a competitive sensor system, the CCd camera, became commercially available. In the present paper we will give an overview and, if necessary, a closer look of the differentitems of both technologies. Advantages and limitations of both systems are discussed. This discussion is not based on pure theory but mostly on real experiences. Therefore a couple of industrial applications are shown. In conclusion we will give an outlook on future developments in sensor technology and evaluation techniques. © 1990 Elsevier Science Publishers B.V.

关键词： 2-d signal processing CCd-camera laser scanning Surface inspection

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Improvement of Recovery in Segmentation-Based Parallel Compressive Sensing

Improvement of Recovery in Segmentation-Based Parallel Compr...

引用

IEEE International Symposium on signal processing and Information Technology (ISSPIT)

作者： Mitra, dipayan Zanddizari, Hadi Rajan, Sreeraman Carleton Univ Dept Syst & Comp Engn Ottawa ON Canada Univ S Florida Dept Elect Engn Tampa FL USA

ISBN: (纸本)9781538675687

This paper extends the recently introduced 1-d Kronecker-based Compressive Sensing (CS) recovery technique to 2-d signals and images. Traditionally large sensing matrices are used while compressing images using CS. CS when applied to individual columns of the image instead of the entire image during the sensing phase, leads to smaller sensing matrices and reduction in computational complexity. For achieving further reduction in computational complexity, the column vectors are further segmented into smaller length segments and CS is applied to each of the smaller length segments. This segmentation process reduces quality of the recovered signal. To enhance the quality of the recovered signal, the entire column vector is recovered using the Kronecker-based CS recovery technique. Magnetic Resonance (MR) images from NCIGT database were used to demonstrate the superiority of the Kronecker-based recovery for 2-d images. Structural similarity and reconstruction error were used to compare the results obtained from Kronecker-based recovery technique with non-Kronecker-based repeated recovery applied to each segments individually. Kronecker-based recovery showed improvement over non-Kronecker-based individual recovery even at higher CR.

关键词： Compressive Sensing Image processing Kronecker Product signal Recovery 2-d signal processing

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