Nonnegative Least-Mean-Square Algorithm

作者：Chen Jie^*; Richard Cedric; Bermudez Jose Carlos M; Honeine Paul

来源：IEEE Transactions on Signal Processing, 2011, 59(11): 5225-5235.

DOI：10.1109/TSP.2011.2162508

• Adaptive filters
• adaptive signal processing
• least mean square algorithms
• nonnegative constraints
• transient analysis

Dynamic system modeling plays a crucial role in the development of techniques for stationary and nonstationary signal processing. Due to the inherent physical characteristics of systems under investigation, nonnegativity is a desired constraint that can usually be imposed on the parameters to estimate. In this paper, we propose a general method for system identification under nonnegativity constraints. We derive the so-called nonnegative least-mean-square algorithm (NNLMS) based on stochastic gradient descent, and we analyze its convergence. Experiments are conducted to illustrate the performance of this approach and consistency with the analysis.

• 出版日期2011-11