Nonparametric identification of a Wiener system using a stochastic excitation of arbitrarily unknown spectrum

Keyphrases

• Nonparametric Identification 100%
• Stochastic Excitation 100%
• Wiener System 100%
• Mean-variance 66%
• Linear Dynamics 66%
• Nonlinear Subsystems 66%
• Convergence Rate 33%
• Monte Carlo Simulation 33%
• Gaussian Noise 33%
• Time-invariant 33%
• Asymptotically Stable 33%
• Nonlinear Static 33%
• Invertible 33%
• Paper-based 33%
• Finite Sample 33%
• Zero Mean 33%
• Linear Systems 33%
• Memoryless 33%
• Unknown Variance 33%
• Invertibility 33%
• Dynamic Time 33%
• Asymptotic Unbiasedness 33%
• System Estimator 33%
• Variance Spectrum 33%
• Asymptotically Unbiased 33%
• Nonzero Mean 33%
• Stable Subsystems 33%
• Internal Signal 33%

Computer Science

• Monte Carlo Simulation 100%
• Internal Signal 100%
• Dynamic Subsystem 100%
• Linear Systems 100%
• Convergence Rate 100%
• Gaussian White Noise 100%

Mathematics

• Stochastics 100%
• Subsystems 100%
• Mean Variance 10%
• Linear System 10%
• Pointwise 10%
• Unbiasedness 10%
• Memoryless 10%
• Parametric 10%
• Variance 10%
• Asymptotic Analysis 10%
• Convergence Rate 10%
• Monte Carlo 10%
• Invertibility 10%
• Random Noise 10%