搜索资源列表
AnadaptiveKalmanfilterfordynamicharmonicstateestim
- Knowledge of the process noise covariance matrix is essential for the application of Kalman filtering. However, it is usually a difficult task to obtain an explicit expression of for large time varying systems. This paper looks at an adaptive
RobustadaptiveKalmanfilteringwithunknowninputs
- The standard optimum Kalman filter demands complete knowledge of the system parameters, the input forcing functions, and the noise statistics. Several adaptive methods have already been devised to obtain the unknown information using the measur
1
- 研究自适应抵消技术的论文，文章很详细的分析并对比了各种自适应噪声抵消技术，且有仿真结果-Adaptive offset technology research papers, articles, very detailed analysis and comparison of various adaptive noise cancellation technology, and simulation results are
Adptve-BF-techniques
- This document is about research area of noise reduction techniques. Here the research area is in adaptive beam forming techniques
adaptive-lms
- 有源自适应噪声的最常用算法，该算法是基于滤波器的输出信号与期望响应之间的误差的均方值为最小。-Active adaptive noise most commonly used algorithm, which is based on the error between the filter output signal and the desired response minimum mean-square value.
adaptive-rms
- 有源自适应噪声的最常用算法之一，该算法是另一个基于最小二乘准则的精确方法，它具有快速收敛和稳定的滤波器特性。-Active adaptive noise, one of the most commonly used algorithm, the algorithm is another accurate method of least squares criterion, it has fast convergence and stability of the filter characteri
SPL_2012_noise
- This a demo program for the paper J. Tian and L. Chen, "Image noise estimation using a variation-adaptive evolutionary approach," IEEE Signal Processing Letters, Vol. 19, No. 7, Jul. 2012, pp. 395-398.- This is a demo program for the paper
mb_ftracker
- Abstract—Several algorithms have been developed for tracking formant frequency trajectories of speech signals, however most of these algorithms are either not robust in real-life noise environments or are not suitable for real-time implementati