Explore MATLAB source code curated for "实验数据" with clean implementations, documentation, and examples.
Ridgelet tools, associated experiments, and related experimental data serve as critical source code for implementing ridgelet applications, providing essential algorithmic foundations and implementation approaches.
Shared experimental datasets and practical software implementations for Bayes classifiers, featuring algorithm explanations and code integration details for effective machine learning applications.
Applying the Danish Method for robust estimation of experimental data, suitable for datasets containing gross errors or outliers, with implementation insights into weighting strategies and iterative refinement.
Comprehensive experimental datasets and MATLAB code examples for analyzing performance metrics of various battery types, including lithium-ion, lead-acid, and nickel-metal hydride batteries, featuring voltage characteristics, capacity measurements, and discharge rate analysis.
Applying the Danish Method for Robust Estimation of Experimental Data with Code Implementation Insights
Implementation of Genetic Algorithm for BP Neural Network Optimization with Enhanced Performance Characteristics