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fundamental

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NLS algorithm for estimation has been implemented successfully and has provided good estimates for all range of frequencies. It has also been tested for different sampling frequencies and this estimator is better compared to autocorrelation method as it doesn’t require any pre-processing. The NLS method is statistically efficient if the noise is modelled as white and Gaussian and much more accurate than the autocorrelation based methods. But a drawback of this algorithm is that it takes time to calculate the cost function matrix as it involves matrix multiplication with an inverse matrix. This method can be made faster if implemented using recursive solver for Toeplitz-plus-Hankel systems for computing NLS cost function.

  • Updated Feb 7, 2019
  • Python

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