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Improved gradient descent algorithms for time-delay rational state-space systems: intelligent search method and momentum method
Improved gradient descent algorithms for time-delay rational state-space systems: intelligent search method and momentum method
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Improved gradient descent algorithms for time-delay rational state-space systems: intelligent search method and momentum method
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Improved gradient descent algorithms for time-delay rational state-space systems: intelligent search method and momentum method
Improved gradient descent algorithms for time-delay rational state-space systems: intelligent search method and momentum method

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Improved gradient descent algorithms for time-delay rational state-space systems: intelligent search method and momentum method
Improved gradient descent algorithms for time-delay rational state-space systems: intelligent search method and momentum method
Journal Article

Improved gradient descent algorithms for time-delay rational state-space systems: intelligent search method and momentum method

2020
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Overview
This study proposes two improved gradient descent parameter estimation algorithms for rational state-space models with time-delay. These two algorithms, based on intelligent search method and momentum method, can simultaneously estimate the time-delay and parameters without the matrix eigenvalue calculation in each iteration. Compared with the traditional gradient descent algorithm, the improved algorithms come with two advantages: having quicker convergence rates and less computational efforts, particularly meaningful for those large-scale systems. A simulated example is selected to illustrate the efficiency of the proposed algorithms.