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A new approach to time frequency transform and pattern recognition of non-Stationary power signals is presented in this paper. In the proposed work Visual localization, detection and classification of non-stationary power signals are achieved using HS-Transform and automatic pattern recognition is carried out using fuzzy C-means based Genetic algorithm.(More)
The paper presents an adaptive Unscented Kalman Filter (AUKF) for the estimation of non-stationary signal amplitude and frequency in the presence of significant noise and harmonics. The initial choice of the model and measurement error covariance matrices Q and R along with other UKF parameters is performed using a modified Particle Swarm Optimization (PSO)(More)
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