Paper
21 September 1998 New global-search method for designing filter banks
Yi Shang, Benjamin W. Wah
Author Affiliations +
Abstract
In this paper, we present a new global-search method for designing QMF (quadrature-mirror-filter) filter banks. We formulate the design problem as a nonlinear constrained optimization problem, using the reconstruction error as the objective, and the other performance metrics as constraints. This formulation allows us to search for designs that improve over the best existing designs. Due to the nonlinear nature of the performance metrics, the design problem is a nonlinear constrained optimization problem with many local minima. We propose to solve this design problem use global- search methods based on Lagrangian formulations. After transforming the original constrained optimization problem into an unconstrained form using Lagrange multipliers, we apply a new global-search method to find good solutions. The method consists of a coarse-level global-search phase, a fine-level global-search phase, and a local search phase, and is suitable for parallel computation due to the minimal dependency between various key components. In our experiments, we show that our method finds better designs than existing global-search methods, including simulated annealing and genetic algorithms.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yi Shang and Benjamin W. Wah "New global-search method for designing filter banks", Proc. SPIE 3452, Parallel and Distributed Methods for Image Processing II, (21 September 1998); https://doi.org/10.1117/12.323461
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KEYWORDS
Nonlinear filtering

Optical filters

Linear filtering

Filtering (signal processing)

Electronic filtering

Algorithms

Information operations

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