在各种传输系统中，横向滤波器的结构被广泛采用。
The structure of landscape orientation filter is often used in many kinds of transmission systems.
通常采用LMS算法对自适应横向滤波器的加权系数进行调节。
The LMS algorithm is usually adopted to adjust weight coefficients of the adaptive transversal filter whose output is an estimation of the echo signal.
该文讨论了用横向滤波器实现MTD雷达中多普勒数字滤波器组的硬件结构和实现方法。
This paper discusses the hardware structure and implementation of DopplerfiIter bank in MTD radar using transversal filter.
在MSE准则下，设计了一个定长的自适应最小均方横向滤波器，并通过MATLAB编程实现。
Afterward according to the MSE rule, we design a limited length transversal filter, and implement by MATLAB.
算法在格型预测器部分采用快速RLS算法，而在自适应横向滤波器部分采用LMS算法，并加以适当改进。
For the proposed one we use the fast RLS algorithm in lattice predictive filtering part with some modification and the LMS in adaptive transversal filtering part.
神经网络作为一种新型的优化算法，可以替代自适应均衡算法中的横向滤波器，在数字通信系统中得到了广泛应用。
As a kind of new optimized algorithm, neural network can substitute for landscape orientation filter in adaptive equalization, and it has been widely used in digital communication system.
训练阶段的相关算法与工作阶段的LMS算法可结合在同一个横向滤波器结构中，从而加速了自适应信道估计器的收敛过程。
The correlation algorithm in training period and the LMS algorithm in run period can be combined in the identical transversal filter structure, so that it speeds up the channel estimator convergence.
着重介绍采用最小均方算法的横向滤波器、判决反馈均衡器及盲均衡器，讨论了HDTV中采用的不同均衡方案及其均衡性能。
The emphasis is laid on the principles of LMS transversal filter, decision feedback equalizer and blind equalizer. Different equalizing schemes and their performance used in HDTV are discussed.
另一方面针对IFOG输出信号具有时变特性的特点，提出了自适应滤波方案，并设计了基于LMS算法的自适应横向滤波器。
On the other side, a transverse adaptive filter based on the LMS was designed according to the time-varying characteristic of IFOG output signals.
本文设计的均衡器采用了时域和频域联合处理的自适应均衡技术，其中频域均衡作为DFE的前馈滤波部分，时域的反馈滤波的部分使用常规的横向滤波器。
The equalization in frequency domain is the feed-forward filtering of the DFE. And the traditional transversal filter is used in the feed-back filtering in time domain.
该方法是将拾振器的输出信号作为FIR横向滤波器的输入，用自适应rls算法对FIR横向滤波器系数进行辨识而最终获得可以恢复拾振器原始输入信号的反卷积滤波器。
The coefficients of the FIR transversal filter was identified by using adaptive RLS algorithm while the output signal of the vibration pick-up was input into the FIR transversal filter.
该方法是将拾振器的输出信号作为FIR横向滤波器的输入，用自适应rls算法对FIR横向滤波器系数进行辨识而最终获得可以恢复拾振器原始输入信号的反卷积滤波器。
The coefficients of the FIR transversal filter was identified by using adaptive RLS algorithm while the output signal of the vibration pick-up was input into the FIR transversal filter.
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