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This document presents a method for dynamic state estimation that combines Particle Filter (PF) and Adaptive Vector Quantization (AVQ) using a competitive reinitialization learning (CRL) algorithm. The proposed method improves the extraction of information from probability density distributions by utilizing all particles in PF, leading to rapid adaptation and robustness in time-varying environments. Simulations demonstrate the effectiveness of the method in approximating complex probability distributions an

Author

ashraf faraj

Language

EN