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In this paper we develop qubit Hamiltonian single parameter estimation techniques using Bayesian approach. The algorithms considered are restricted to projective measurements in a fixed basis, and are derived under the assumption that the qubit measurement is much slower than the characteristic qubit evolution. The non-adaptive algorithm is optimized using particle swarm optimization and compared...
A new method with an efficient parallel particle swarm optimization (PSO) algorithm is proposed for estimating motion parameters. Compared with the traditional methods, modified parallel PSO algorithm features such as easily realizing in parallel machines and ability of global search are demonstrated. The experiments give the performance of algorithm, which could satisfy the desire in the system of...
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