Steady State Analysis of Two-Dimensional LMS Adaptive Filters Using the Independence Assumption
نویسندگان
چکیده
In this paper, we consider the steady state Mean Square Error (MSE) analysis for 2-D LMS algorithm in which the filter's weights are updated in both vertical and horizontal directions using Fornasini and Marchesini (F-M) state space model. The MSE analysis is conducted using the wellknown independence assumption. First we show that computation of the Weight-Error Correlation Matrix (WECM) for F-M model-based 2-D LMS algorithm requires an approximation for the WECMs at large spatial lags. Then we propose a method to solve this problem. Further discussion is carried out for the special case when the input signal is white Gaussian. It is shown that a more strict condition on the upper bounds of the used step size values is required to ensure the convergence of the 2-D LMS in the MSE sense. Simulation experiments are presented to support the obtained analytical results. keywords: 2-D LMS, steady state analysis, mean square error.
منابع مشابه
Steady State Analysis of 2-D LMS Adaptive Filters Using the Independence Assumption
In this paper, we consider the steady state mean square error (MSE) analysis for 2-D LMS adaptive filtering algorithm in which the filter’s weights are updated along both vertical and horizontal directions as a doubly-indexed dynamical system. The MSE analysis is conducted using the well-known independence assumption. First we show that computation of the weight-error covariance matrix for doub...
متن کاملIterative analysis of the steady-state weight fluctuations in LMS-type adaptive filters
An iterative method is proposed for the analysis of the steadystate weight fluctuations in an LMS-type adaptive FIR filter. Without the widely used independence assumption, a power series of the weighterror correlation matrix is derived in terms of the stepsize. Some new effects are observed, e.g., a decrease of the weight fluctuations along the tapped-delay line.
متن کاملSpeech Enhancement by Modified Convex Combination of Fractional Adaptive Filtering
This paper presents new adaptive filtering techniques used in speech enhancement system. Adaptive filtering schemes are subjected to different trade-offs regarding their steady-state misadjustment, speed of convergence, and tracking performance. Fractional Least-Mean-Square (FLMS) is a new adaptive algorithm which has better performance than the conventional LMS algorithm. Normalization of LMS ...
متن کاملSecond moment analysis of the filtered-X LMS algorithm
Active noise and vibration control (ANC) has become an important application area for adaptive filters. The most popular adaptive algorithm used for ANC is the Filtered-X LMS (FXLMS) algorithm [1,2]. This algorithm is a modification of the well known LMS algorithm. The reference signal is filtered so as to compensate for filters inherent in the electro-acoustic adaptation loop. These additional...
متن کاملImage Restoration with Two-Dimensional Adaptive Filter Algorithms
Two-dimensional (TD) adaptive filtering is a technique that can be applied to many image, and signal processing applications. This paper extends the one-dimensional adaptive filter algorithms to TD structures and the novel TD adaptive filters are established. Based on this extension, the TD variable step-size normalized least mean squares (TD-VSS-NLMS), the TD-VSS affine projection algorithms (...
متن کامل