Explore MATLAB source code curated for "数据" with clean implementations, documentation, and examples.
A MATLAB GUI application that captures data from edit boxes through button clicks and displays it in static text fields, demonstrating callback function implementation and UI component interaction.
k-means Outlier Removal Method: Primarily employs clustering mean approach to eliminate outliers from data, enhancing model prediction accuracy. This article provides MATLAB implementation code with cluster center analysis and distance-based outlier detection mechanisms.
The EEG and ECG datasets have been preprocessed using MATLAB and can be directly loaded via the load function for immediate analysis
Traffic prediction program implemented with BP algorithm, including dataset and full source code. The program is ready-to-run with straightforward execution process.
MATLAB implementation of sliding window detection for small targets in Gaussian noise environments. The dataset contains 1000 data points with a window size of 30, shifting one point per iteration. The algorithm squares each of the 30 data points within the window, sums them up, and divides by the window size. Experimental results demonstrate effective radar target signal detection. Key implementation involves using moving window functions and power calculation methods.
A MATLAB program implementing wavelet packet decomposition and signal reconstruction, thoroughly tested with custom datasets
Fully functional MATLAB implementation of Ant Colony Optimization algorithm including complete source code, detailed documentation, pre-configured simulation data and parameter values. This serves as an excellent educational resource for understanding and applying ACO algorithms.
Interferometric Synthetic Aperture Radar (InSAR) Data: ERS-acquired coherence amplitude and interferometric phase data for a mountainous region, stored in MATLAB .mat format with ready-to-process structure for deformation analysis
Exploratory Data Analysis (EDA) Process and Implementation
A comprehensive guide to white noise generation methods, including fully debugged implementations with complete datasets and code examples.