虽然判决导引最小均方误差算法(DD -LMS)剩余误差小，但是，在信道眼图闭合的情况下，该算法无法收敛，即不具备冷启动能力。
Though the decision directed least mean square error algorithm (DD-LMS) has small residual error, when the channel eye close, it can not converge. That is, it has no cold start ability.
实验表明该方法融合结果的均方误差比拉普拉斯金字塔算法和小波变换方法降低约30%- 60%。
The experimental results demonstrate that the MSE (mean square error) reduced by this proposed approach decreases 30% - 60% than that by Laplacian pyramid and discrete wavelet transform approaches.
此算法相对于均方误差最小准则和最大误差最小化准则具有占用存储空间小和计算时间短的优点。
Compared with the minimum mean squared error principle and the minimaxs principle this one needs smaller memory space and less computation time.
该方法计算简单、均方误差小、收敛速度快，并且降低了算法对噪声的敏感性。
It obtains low average mean squared error (MSE), fast convergence velocity and decreases the noise sensitivity at the same time.
该方法计算简单、均方误差小、收敛速度快，并且降低了算法对噪声的敏感性。
It obtains low average mean squared error (MSE), fast convergence velocity and decreases the noise sensitivity at the same time.
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