基于线性代数与矩阵理论，给出利用LDLT分解计算实对称矩阵特征值的递归算法。
A recursive algorithm for calculating the eigenvalues of a real symmetric matrix based on LDLT decomposition is given.
理论分析和计算机仿真实验均表明，新算法与传统的恒模算法相比，具有更快的收敛速度和更小的稳态剩余误差。
The theoretical analysis and the simulation results proved to show that the new algorithm has improved performance of the convergence speed and residual error than traditional CM algorithm.
理论分析和计算机仿真实验均表明该算法与传统的恒模算法相比，都具有更快的收敛速度和更小的稳态剩余误差。
Theoritical analyse and computer simulation both shows the new one has faster convergent speed and less steady error than traditional constant-modulus algorithms.
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