Joint Diagonalization of Matrix Based on Improved Genetic Algorithm
基于改进遗传算法的矩阵联合对角化

The paper simplifies the joint diagonalization of matrices into optimization problem which only includes the eigen matrix. For solving the problem conveniently, each row vector of the eigen matrix is parameterized, then utilizes the improved genetic algorithm to get the optimal parameter. The algorithm improves the choose of chromosome and probability of cross with variation, introduces simulated anneal technology into operator of crossing and variation. Finally it unifies the gradient algorithm to seek local optimality. The simulation result verify the algorithm.