Analysis of Finite-precision Effect of TDNLMS Adaptive Predictor and its Application in Digital Filter Design
TDNLMS自适应预测器有限字长效应分析及其在设计中的应用

The TDNLMS (two dimensional normalized least mean squared error) adaptive filter can be used as a pre whitening filter in small object detection application in digital image. The performance of the digital implementation of the adaptive filter is influenced by the finite precision effect. In this paper, the finite-precision effect of TDNLMS adaptive predictor used for small objects detection is analyzed, and a method of determining computation word length of the digital adaptive filter by experiments is presented. The relation between the word length of the adaptive predictor and the features of the environment, including the step size parameter, input data word length, statistic characteristic of image processed and the support region of the predictor, is discussed. Simulation results are consistent with the analysis. Through the method presented in this paper, a finite precision TDNLMS adaptive predictor is designed, and compared with an infinite precision predictor witch is implemented by double precision floating point numbers. Simulation results shown that the MSE (mean squared error) and the mean SNR (signal to noise ratio) gain produced by the finite precision TDNLMS adaptive predictor is very close to the infinite precision TDNLMS adaptive predictor.