本文提出了一种利用相邻QRS波的相关性进行最小均方差预测的心电图压缩算法。
A novel electrocardiogram compression algorithm based on minimum root-mean-square error prediction utilizing the correlation of adjacent QRS wave is proposed.
该算法主要通过控制平滑区域大小和均方差阈值来选择受噪声干扰最小和最大相关区域。
The algorithm mainly controls the size of the smoothing area and the mean variance threshold to select the maximum correlation area containing minimum noise interference.
本文讨论了一种带有参考通道的自适应话音消噪滤波器原理，该滤波器采用最小均方差(LMS)算法。
In the paper, a kind of adaptive noise cancellation filter with reference channel based on Least Mean Square (LMS) algorithm is discussed.
这个实现是基于规格化最小均方差(NLMS)的算法，包括双端语音活动检测的原理。
This implementation is based on the Normalized Least Mean Square (NLMS) algorithm. The algorithm includes double-talk detection.
与已有线性最小均方差(LMMSE)信道估计方法相比，该算法简单并且不需要预先知道信道相关矩阵以及信噪比等信道信息。
Comparing with the Linear Minimum Mean Square Error (LMMSE) channel estimation method, the method is simple and need not know the channel correlation and signal-to-noise (SNR).
该算法采用协方差匹配技术，依据滤波新息，动态调整测量噪声方差，使融合系统的均方误差始终最小。
With covariance matching technique and innovation information of filtering, the noise variance is dynamically adjusted and the mean square error of the fusion system always keeps minimum.
介绍一种基于改进的可变步长规格化最小均方差(NLMS)回声消除算法研究和它的DSP实现。
The paper introduces acoustic echo cancellation algorithm that is based on the improved and variable step size NLMS and it's DSP implementation.
这两种滤波算法均保持了线性方差最小意义下的最优性。
It is optimal still in the sense of linear minimum-variance.
反馈联合检测算法通常可为迫零数据块判决反馈均衡器（ZF-BDFE）和最小均方差数据块判决反馈均衡器（MMSE-BDFE）算法。
The feedback joint detection algorithms mainly comprise zero forcing block decision feedback equalizer (ZF-BDFE) and minimum mean-square-error block decision feedback equalizer (MMSE-BDFE).
反馈联合检测算法通常可为迫零数据块判决反馈均衡器（ZF-BDFE）和最小均方差数据块判决反馈均衡器（MMSE-BDFE）算法。
The feedback joint detection algorithms mainly comprise zero forcing block decision feedback equalizer (ZF-BDFE) and minimum mean-square-error block decision feedback equalizer (MMSE-BDFE).
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