Amit Kumar Naik

About

Born in 1994, in Raigarh, India, Amit Kumar NAIK is a research scholar at IIT Indore, Indore, India. His research interests involve the domain of estimation and filtering. He is working towards developing new filtering algorithms to tackle the irregularities present in the measurements.

Employment

Employment history is unavailable.

Education

• Indian Institute of Technology Indore Ph.D.
  2019 - Present

Projects & Funding

Projects & funding information is unavailable.

Publications (7)

• Gaussian Filtering With Stochastically Composed Current and Past Measurements
  Amit Kumar Naik, Neelanshu Garg, Prabhat K. Upadhyay

  +1 more

  • Abhinoy Kumar Singh
  IEEE Transactions on Automation Science and Engineering 2026 DOI: 10.1109/TASE.2025.3639904
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• Kalman‐based multiple sinusoids identification from intermittently missing measurements of the superimposed signal
  Amit Kumar Naik, Sumanta Kumar Nanda, Prabhat K. Upadhyay

  +1 more

  • Abhinoy Kumar Singh
  International Journal of Adaptive Control and Signal Processing 2024 DOI: 10.1002/acs.3853
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• Gaussian Filtering With Cyber-Attacked Data
  Guddu Kumar, Amit Kumar Naik, R Swaminathan +1 more
  IEEE Signal Processing Letters 2024 DOI: 10.1109/LSP.2024.3356825
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• Gaussian kernel quadrature Kalman filter
  Amit Kumar Naik, Prabhat K. Upadhyay, Abhinoy Kumar Singh
  European Journal of Control 2023 DOI: 10.1016/j.ejcon.2023.100805
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• Gaussian Filtering With False Data Injection and Randomly Delayed Measurements
  Sumanta Kumar Nanda, Guddu Kumar, Amit Kumar Naik +4 more
  IEEE Access 2023 DOI: 10.1109/ACCESS.2023.3305288
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• Nonlinear Filtering With Sporadically Missing Sensor Data
  Amit Kumar Naik, Prabhat K. Upadhyay, Maurizio Magarini

  +1 more

  • Abhinoy Kumar Singh
  IEEE Sensors Letters 2023 DOI: 10.1109/LSENS.2023.3316929
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• Gaussian Filtering for Simultaneously Occurring Delayed and Missing Measurements
  Amit Kumar Naik, Guddu Kumar, Prabhat K. Upadhyay

  +2 more

  • Paresh M Date
  • Abhinoy Kumar Singh
  IEEE Access 2022 DOI: 10.1109/access.2022.3208119
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