Based on tradition filtering algorithm, an adaptive filtering algorithm based on vector space model is proposed in the paper.
在传统过滤算法的基础上，本文提出一种基于向量空间模型的自适应过滤算法。
The goal that researchers are pursuing is to find an adaptive filtering algorithm that converges fast and has low arithmetic complexity.
寻求收敛速度快，计算复杂度低，数值稳定性好的自适应滤波算法是研究人员不断努力追求的目标。
An adaptive binarization filter Algorithm is presented, which combines adaptive filtering with local threshold binarization method.
提出一种灰度文本图像自适应二值化滤波算法。
An interacting multiple model (IMM) adaptive filtering algorithm based on expected system noise model was presented.
本文提出基于期望系统噪声模型的自适应交互式多模型(IMM)算法。
Second, an Enhanced Phase Locked Loop (EPLL) control strategy based on improved Adaptive Notch Filtering (ANF) is proposed, controller parameters are optimized using BF-PSO algorithm.
其次，提出了一种基于改进型ANF的三相EPLL控制策略，并用BF-PSO算法对控制器参数进行优化设计。
Based on the adaptive Kalman filtering algorithm, an estimator for the GPS PN code tracking error with model bias is proposed.
在自适应卡尔曼滤波算法的基础上提出了一种带模型偏差的GPS伪码跟踪误差估计器。
The adaptive Kalman filtering (AKF) based on intelligent information fusion algorithm has currently became an effective approach to enhance the integrated navigation system's robustness and accuracy.
针对当前自适应组合导航系统算法的研究趋势，总结了卡尔曼滤波技术的缺陷和利用智能融合技术提高滤波器性能的设计思想。
An algorithm of adaptive fuzzy Kalman filtering is presented.
提出了一种模糊自适应卡尔曼滤波算法。
Based on the extremum median filter, an auto-adaptive image filtering algorithm is proposed.
在已有极值中值的滤波算法的基础上，提出一种自适应滤波算法。
To improve the performance of LMS adaptive filtering algorithm, an improved variable-step LMS algorithm is proposed based on analysis of existing algorithms.
为了提高LMS自适应滤波算法的性能，在分析已有变步长算法的基础上进行了一些改进。
An adaptive speckle filtering algorithm is proposed. It detects image points belonging to edge based on wavelet transform. Speckle are filtered according to detect results and multi-look.
提出了一种自适应斑点滤波算法，它基于小波变换检测图像中的边缘点，根据检测结果结合多视处理实现斑点滤波。
For state estimation of hybrid system with unknown transition probabilities, an adaptive estimation algorithm is proposed based on Monte Carlo particle filtering.
在算法的状态估计阶段，采用混合系统粒子滤波和二元估计算法同时估计对象系统故障演化模型混合状态和未知参数的后验分布。
For state estimation of hybrid system with unknown transition probabilities, an adaptive estimation algorithm is proposed based on Monte Carlo particle filtering.
在算法的状态估计阶段，采用混合系统粒子滤波和二元估计算法同时估计对象系统故障演化模型混合状态和未知参数的后验分布。
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