Cost function adaptation: a stochastic gradient algorithm for data echo cancellation

作     者：Rusu, C Cowan, CFN 

作者机构：Tampere Univ Technol Digital Media Inst Signal Proc Lab FIN-33101 Tampere Finland Tech Univ Cluj Napoca Dept Elect & Telecommun Cluj Napoca Romania Queens Univ Belfast Dept Elect & Elect Engn Belfast BT9 5AH Antrim North Ireland 

出 版 物：《IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING》 (IEE Proc Vision Image Signal Proc)

年 卷 期：2000年第147卷第6期

页      面：516-526页

核心收录：

主　　题：.steady state stochastic gradient cancellation cost functions films algorithm echo canceller Signal Process 

摘      要：A family of stochastic gradient algorithms and their behaviour in the data echo cancellation work platform are presented. The cost function adaptation algorithms use an error exponent update strategy based on an absolute error mapping, which is updated at every iteration. The quadratic and nonquadratic cost functions are special cases of the new family. Several possible realisations are introduced using these approaches. The noisy error problem is discussed and the digital recursive filter estimator is proposed. The simulation outcomes confirm the effectiveness of the proposed family of algorithms.