具有对数自适应后悔的通用MMSE滤波
Universal MMSE Filtering With Logarithmic Adaptive Regret
摘要:
我们考虑的问题,在线估计的实值信号被遗忘的零均值噪声使用线性估计。该估计器需要根据当前和最后几个噪声观测值迭代地预测潜在信号,其性能由均方误差来衡量。我们描述和分析了这个任务的算法:1。实现对数自适应后悔对最好的线性滤波器在事后。这个界限是近似紧的,并且解决了Moon和Weissman的问题[1]。2.根据滤波器系数的数量在线性时间内进行迭代。以前的建筑至少需要二次时间。
英文摘要:
We consider the problem of online estimation of a real-valued signal corrupted by oblivious zero-mean noise using linear estimators. The estimator is required to iteratively predict the underlying signal based on the current and several last noisy observations, and its performance is measured by the mean-square-error. We describe and analyze an algorithm for this task which: 1. Achieves logarithmic adaptive regret against the best linear filter in hindsight. This bound is assyptotically tight, and resolves the question of Moon and Weissman [1]. 2. Runs in linear time in terms of the number of filter coefficients. Previous constructions required at least quadratic time.
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