Support vector machines based detection for holographic data storage systems

Keskinöz, Mehmet and Lakshmi, Ramamoorthy and Vijaya Kumar, B. V. K. (2005) Support vector machines based detection for holographic data storage systems. In: ICASSP 2005, Philadelphia

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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.
Item Type: Papers in Conference Proceedings
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Mehmet Keskinöz
Date Deposited: 13 Oct 2005 03:00
Last Modified: 26 Apr 2022 08:36
URI: https://research.sabanciuniv.edu/id/eprint/1438

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