In this correspondence, we describe gradient-based adaptive algorithms within parameter spaces that are specified by ∥w∥ = 1, where ∥·∥ is any vector norm. We provide several algorithm forms and relate them to true gradient procedures via their geometric structures. We also give algorithms that mitigate an inherent numerical instability for L2-norm-constrained optimization tasks. Simulations showing the performance of the techniques for independent component analysis are provided.
|Original language||English (US)|
|Number of pages||5|
|Journal||IEEE Transactions on Signal Processing|
|State||Published - 2000|
All Science Journal Classification (ASJC) codes
- Signal Processing
- Electrical and Electronic Engineering