A Class of Weighted Quantized Kernel Recursive Least Squares Algorithms

作者：Wang, Shiyuan^*; Wang, Wanli; Duan, Shukai

来源：IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2017, 64(6): 730-734.

DOI：10.1109/TCSII.2016.2603193

• Adaptive dictionary
• quantized kernel recursive least squares (QKRLS)
• sparsification
• steepest descent method

In this brief, a class of weighted quantized kernel recursive least squares (WQKRLS) algorithms is proposed to efficiently improve the performance of online applications. In the proposed WQKRLS, an online vector quantization with weighted outputs is incorporated into quantized kernel recursive least squares. The resulting desired outputs are smoothed by exponential weights. In addition, the members of the dictionary are updated by the steepest descent method for further performance improvement. Simulations illustrate the superior performance of the proposed WQKRLS.

• 单位
  西南大学