Support vector machines based data detection for holographic data storage systems

Lakshmi Ramamoorthy*, Mehmet Keskinoz, B. V.K.Vijaya Kumar

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Nonlinear nature of Holographic Data Storage Systems (HDSS) suggests that nonlinear equalization and detection techniques may be beneficial. Complexity involved in nonlinear methods does not often make them practical solutions. Support Vector Machines (SVMs) are recently being studied for pattern recognition applications. We investigated linear SVM detection and observed that the Bit Error Rate (BER) using SVM for data detection on Linear Minimum Mean Squared Error (LMMSE) equalized holographically recorded and retrieved 2-D data pages is about 17% better than the simple threshold detection on unequalized pages.

Original languageEnglish
Title of host publication2005 IEEE International Conference on Acoustics, Speech, and Signal Processing,ICASSP '05 - Proceedings - Audio and ElectroacousticsSignal Processing for Communication
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages969-972
Number of pages4
ISBN (Print)0780388747, 9780780388741
DOIs
Publication statusPublished - 2005
Externally publishedYes
Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
Duration: 18 Mar 200523 Mar 2005

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
VolumeIII
ISSN (Print)1520-6149

Conference

Conference2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Country/TerritoryUnited States
CityPhiladelphia, PA
Period18/03/0523/03/05

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