Mahalanobis Distance for Outlier Detection
The Mahalanobis distance effectively removes outlier samples by identifying deviations from data distribution patterns - simply update your dataset parameters for implementation
Several Pattern Recognition Methods with MATLAB Implementation
Implementation of multiple pattern recognition algorithms in MATLAB including Chebyshev distance method, Mahalanobis distance method, and Euclidean distance method, each provided with various programming approaches and detailed code explanations.
Enhanced Data Association Process in SLAM Algorithm
This paper presents a practical improvement for the data association process in SLAM algorithms by combining Euclidean distance with Mahalanobis distance. The algorithm efficiently narrows down the search scope for feature matching by first applying simpler Euclidean distance calculations before computing more complex Mahalanobis distances. Simulation results using synthetic data demonstrate that our enhanced method significantly reduces computational load and improves association efficiency without increasing incorrect associations.
Computing Mahalanobis Distance for Images Using MATLAB
Implementing Mahalanobis distance calculation for image analysis using MATLAB
Calculating Mahalanobis Distance with Algorithm Implementation
A comprehensive guide to computing Mahalanobis distance, including mathematical formulation, code implementation approaches, and preprocessing considerations for robust distance calculation.
MATLAB Code Implementation for Calculating Mahalanobis Distance
MATLAB code implementation for calculating Mahalanobis distance with detailed algorithm explanation and practical applications
Computing Mahalanobis Distance for Statistical Analysis
Implementation of Mahalanobis Distance Calculation with Code Integration for Data Analysis