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Found 6 papers, 1 papers with code
A Family of Robust Generalized Adaptive Filters and Application for Time-series Prediction
The continuous development of new adaptive filters (AFs) based on novel cost functions (CFs) is driven by the demands of various application scenarios and noise environments.
Adaptive Robust Unscented Kalman Filter for Dynamic State Estimation of Power System
Then, GMMEEF-AUKF is developed by solving the optimization problem based on GMMEEF, which uses a generalized Gaussian kernel combined with mixture correntropy to enhance the flexibility further and resolve the data problem with complex attributes and update the noise covariance matrix according to the AREM framework.
Diffusion Augmented Complex Maximum Total Correntropy Algorithm for Power System Frequency Estimation
Moreover, traditional adaptive filtering algorithms designed based on the strictly-linear (SL) model fail to effectively address frequency estimation challenges in unbalanced three-phase power systems.
Robust Square Root Unscented Kalman filter of graph signals
In addition, in order to enhance the numerical stability of the unscented Kalman filter, the algorithm combines the double square root decomposition method to update the covariance matrix in the graph frequency domain.
MIPI 2024 Challenge on Few-shot RAW Image Denoising: Methods and Results
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems.
Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination
Most of the current face hallucination methods, whether they are shallow learning-based or deep learning-based, all try to learn a relationship model between Low-Resolution (LR) and High-Resolution (HR) spaces with the help of a training set.
