A NOVEL APPROACH TO STATE SPACE TIME DOMAIN AUTOREGRESSIVE SIGNAL PROCESSING USING OPTIMAL RECURSIVE ESTIMATOR

  • Jawahar A Department of EEE, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, India.
  • Murali Krishna P Department of Electrical Engineer, National Operation and Maintenance Company Limited, Jeddah, Saudi Arabia.
  • Kiran Ss Department of ECE, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, India.

Abstract

This work describes the concept of filtering of signals using discrete Kalman filter. The true state of constant, random constant having process noise and autoregressive (p) process when corrupted by measurement noise are estimated using discrete Kalman filter and results are presented using MATLAB.

References

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3. Diniz PS. Adaptive Filtering Algorithms and Practical Implementation. New York: Kluwer Academic Publishers; 2013.
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A, J., P, M. K., & Ss, K. (2018). A NOVEL APPROACH TO STATE SPACE TIME DOMAIN AUTOREGRESSIVE SIGNAL PROCESSING USING OPTIMAL RECURSIVE ESTIMATOR. Innovare Journal of Engineering & Technology, 6(1), 6-9. Retrieved from https://innovareacademics.in/journals/index.php/ijet/article/view/16054
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