Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Only few estimation methods can converge in the presence of impulsive measurement and/or process noises without the use of augmented heuristic schemes. To understand the performance of these schemes, the optimal Idan/Speyer Cauchy Estimator (ISCE) is compared with the performance of the particle filter (PF) and Gaussian sum filter (GSF) as the convergence time of these estimators is allod to increase. That is, the number of particles at each step for the PF and the number of Gaussian components at each step for the GSF are increased and their performance relative to the ISCE is numerically studied for scalar and two-state dynamic systems.
['Robert Fonod', 'Moshe Idan', 'Jason L. Speyer']
I am writing a research paper on a idea State estimation for linear systems with additive cauchy noises: Optimal and suboptimal approaches
[{"from": "human", "value": "I am writing a research paper on a idea State estimation for linear systems with additive cauchy noises: Optimal and suboptimal approaches"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Only few estimation methods can converge in the presence of impulsive measurement and/or process noises without the use of augmented heuristic schemes. To understand the performance of these schemes, the optimal Idan/Speyer Cauchy Estimator (ISCE) is compared with the performance of the particle filter (PF) and Gaussian sum filter (GSF) as the convergence time of these estimators is allod to increase. That is, the number of particles at each step for the PF and the number of Gaussian components at each step for the GSF are increased and their performance relative to the ISCE is numerically studied for scalar and two-state dynamic systems."}]