Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  deals with time-varying matrix parameter identification in continuous-time stochastic systems with correlated noise. The forming filter, which generates this noise from a standard white noise, is assumed to be partially known (a nominal plant plus a bounded uncertainty). The least squares method with a scalar forgetting factor (LSMFF) is proposed to be applied for the estimation of these parameters. A numerical example illustrates the effectiveness of the proposed approach.
['J. Escobar', 'Alexander S. Poznyak']
I am writing a research paper on a idea Continuous-time identification using LS-method under colored noise perturbations
[{"from": "human", "value": "I am writing a research paper on a idea Continuous-time identification using LS-method under colored noise perturbations"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  deals with time-varying matrix parameter identification in continuous-time stochastic systems with correlated noise. The forming filter, which generates this noise from a standard white noise, is assumed to be partially known (a nominal plant plus a bounded uncertainty). The least squares method with a scalar forgetting factor (LSMFF) is proposed to be applied for the estimation of these parameters. A numerical example illustrates the effectiveness of the proposed approach."}]