数据处理 Resources

Showing items tagged with "数据处理"

This project implements data processing and error analysis capabilities using MATLAB software. While MATLAB's interface may not be as intuitive as VB, it offers extensive built-in functions that facilitate efficient implementation. The implemented features include: (1) Arithmetic mean calculation; (2) Residual error (absolute error) computation; (3) Standard deviation calculation; (4) Gross error detection and elimination with recalculation; (5) Identification of linear or periodic errors in datasets. The implementation leverages MATLAB's statistical toolbox functions for robust error analysis.

MATLAB 295 views Tagged
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A fuzzy control program developed using MATLAB Simulink toolbox, designed for effective data processing under input uncertainty conditions. Implementation includes fuzzy inference system configuration and rule-based decision making algorithms.

MATLAB 205 views Tagged
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The Kalman Filter is an "optimal recursive data processing algorithm" that provides the most efficient and effective solution for a wide range of problems. It has seen extensive applications for over 30 years in fields including robotic navigation, control systems, sensor data fusion, military radar systems, and missile tracking. In recent years, it has been increasingly applied to computer image processing tasks such as facial recognition, image segmentation, and edge detection. The filter operates through a two-step process: prediction (projecting state estimates forward) and update (correcting estimates with new measurements), typically implemented using matrix operations for state transition and covariance calculations.

MATLAB 234 views Tagged
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GMDH-type Polynomial Neural Network A MATLAB implementation of Group Method of Data Handling (GMDH) for building polynomial neural networks. The algorithm iteratively constructs network layers where the exact architecture (connections) and size (number of layers) are determined automatically during training through evaluation criteria. Validation can use additional test data with regularity criteria or explicit complexity control via information criteria (AIC) or minimum description length (MDL). Key parameters include: number of inputs per neuron, maximum polynomial terms in neurons, cross-layer connections allowing inputs from both previous layers and original variables, and configurable neuron reduction in subsequent layers for optimal network complexity.

MATLAB 200 views Tagged
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ECG Feature Point Detection Technology - Research on Heart Sound Signal Recognition Algorithms with MATLAB Implementation for ECG Data Processing and Electrocardiograph Machine Source Code

MATLAB 250 views Tagged
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Radar target track tracking system - execute the main_test function for radar data processing, ultimately displaying target trajectories with comprehensive algorithm implementation details.

MATLAB 209 views Tagged
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