Simulation Program for MIMO System Capacity and THP Precoding Based on QR Decomposition
Simulation program for analyzing MIMO system capacity and evaluating THP precoding performance using QR decomposition in multi-antenna configurations
Adaptive Genetic Algorithm Implementation
MATLAB source code for adaptive genetic algorithm utilizing Gram-Schmidt orthogonalization decomposition. Users can alternatively implement QR decomposition for potential code simplification and computational efficiency improvements.
QR Decomposition-Based Breadth-First Sphere Decoding (K-Best Algorithm)
Breadth-first sphere decoding based on QR decomposition, commonly known as the K-best algorithm, is designed for signal detection at the receiver end in MIMO technology. This approach employs matrix factorization and candidate selection to enhance decoding efficiency.
Implementation of QR Decomposition Using Modified Gram-Schmidt Algorithm with Advanced Matrix Computations
Comprehensive implementation of QR decomposition via modified Gram-Schmidt algorithm, custom LU decomposition, and eigenvalue computation using power and inverse power methods. Includes practical examples demonstrating algorithm applications with code implementation insights for numerical stability and eigenvalue calculations.
QR Decomposition Using Householder Reflections
QR Decomposition Implementation with Householder Reflections for Matrix Factorization
QR Decomposition Implementation Using Givens Rotations
Algorithm explanation and implementation of QR decomposition through Givens rotations with code-oriented technical insights.
Solving Linear Equations AX=b Using QR Decomposition
Solving AX=b through QR decomposition implemented with Householder transformations for enhanced numerical stability
QR Decomposition
QR Decomposition: Matrix Factorization into Orthogonal and Triangular Components
Givens Rotation Matrix Transformation Algorithm
Implementation and Applications of Givens Rotation Matrix Algorithm for Matrix Transformation