3 results about "Nonlinear noise" patented technology

This invention relates to the field of sensor measurement technology and discloses a multimodal sensor orientation measurement fusion system, aiming to solve the problems of insufficient time synchronization accuracy, limited sensor anomaly detection and compensation capabilities, and degraded fusion performance under nonlinear noise environments in multimodal sensor orientation measurement. The system includes a sensor array module, a spatiotemporal alignment preprocessing module, a multimodal feature extraction and encoding module, an adaptive weighted fusion decision module, and a system output and feedback control module. Through hardware synchronous sampling, phase-locked loop clock compensation, extrinsic parameter calibration, adaptive feature extraction, sensor health assessment, and improved capacitive Kalman filter fusion, combined with a closed-loop correction mechanism, it achieves high-precision, robust, and adaptive orientation measurement, effectively improving state estimation accuracy and system stability.

The application discloses an enhanced model day-ahead electricity price prediction method based on dynamic feature selection, which extracts features from the original data set through a multi-head attention mechanism for multidimensional correlation analysis, generates a feature weight vector in real time to realize dynamic screening of the optimal feature subset, thereby suppressing redundant information and nonlinear noise features at the source; then, an enhanced XGBoost model is used to deeply mine the structured relationship of power market data, simultaneously combined with a Transformer model to capture the long-range time series dependence characteristics of the electricity price sequence, and through a gating mechanism to perform dynamic weighted fusion, to realize the complementary integration of spatial features and time series features; finally, a multi-objective Bayesian optimization algorithm is introduced to obtain a trained enhanced model through multi-objective collaborative optimization, and then prediction is performed. The application significantly improves the prediction accuracy and robustness, effectively solves the deployment problem of the model in a resource-limited environment, and has high engineering application value and power market prediction practicality.

The application relates to the technical field of image processing, and discloses a noise model calibration method, an image denoising method, a device, equipment and a medium. The method comprises the following steps: acquiring multiple RAW domain images; performing nonlinear noise denoising processing based on the multiple RAW domain images to generate a target image; and calibrating a preset RAW domain noise model based on the target image to generate a target RAW domain noise model. Through the technical scheme, the denoising precision of the target RAW domain noise model is improved, and thus the image definition and the image quality of the RAW domain image are improved.