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Updated: Jun 20, 2026

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters
15:25

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

Published on: February 4, 2018

Composite matched filtering with error correction.

R J Marks Ii, L E Atlas

    Optics Letters
    |September 10, 2009
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces an algorithm to improve the accuracy of inexact analog optical processors by treating computation as a communication problem. The method detects and corrects errors, enhancing reliable computation with noisy data.

    Related Experiment Videos

    Last Updated: Jun 20, 2026

    Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters
    15:25

    Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

    Published on: February 4, 2018

    Area of Science:

    • Information theory
    • Computational science
    • Optical computing

    Background:

    • Analog optical processors offer high speed and parallelism but are limited by significant inaccuracies.
    • Traditional computing models assume exact processing, which is not always feasible.
    • Information theory provides a framework for reliable communication over noisy channels.

    Purpose of the Study:

    • To develop an algorithm for improving the accuracy of inexact processors, specifically matched filter processors.
    • To leverage principles from information theory to enhance computational reliability.
    • To address errors arising from noisy data and imprecise computations.

    Main Methods:

    • Framing computational tasks as communication problems.
    • Developing an algorithm for matched filter processors to detect and correct errors.
    • Analyzing the trade-off between accuracy improvement and computational resources.

    Main Results:

    • The proposed algorithm significantly improves the accuracy of matched filter processors.
    • Errors due to noisy data and inexact computing can be effectively detected.
    • In some cases, errors can be corrected, leading to more reliable computations.
    • Accuracy improvements are achieved with a modest increase in computational resources.

    Conclusions:

    • Computational accuracy can be enhanced in inexact processors by applying information theory principles.
    • The developed algorithm offers a practical solution for improving the reliability of analog optical processors.
    • This approach opens possibilities for more robust and accurate computations in systems with inherent inaccuracies.