Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/60469
Title: Gradient flow approach to discrete-time envelope-constrained filter design via orthonormal filters
Authors: Tseng, CH
Teo, KL
Cantoni, A
Zang, Z
Issue Date: 2000
Publisher: The Institution of Engineering and Technology
Source: IEE proceedings. Vision, image, and signal processing, 2000, v. 147, no. 1, p. 79-88 How to cite?
Journal: IEE proceedings. Vision, image, and signal processing 
Abstract: Using digital orthonormal filters and Lagrangian duality theory, the envelope-constrained (EC) filtering problem has been formulated as a dual quadratic programming (QP) problem with simple constraints. Applying the barrier-gradient and barrier-Newton methods based on the space transformation and gradient flow technique, two efficient design algorithms are constructed for solving this QP problem. An adaptive algorithm, based on the barrier-gradient algorithm, is developed to solve the EC filtering problem in a stochastic environment. The convergence properties are established in the mean and mean square error senses. To demonstrate the effectiveness of the proposed algorithms, a practical example using the Laguerre networks is solved for both the deterministic and stochastic cases.
URI: http://hdl.handle.net/10397/60469
ISSN: 1350-245X
EISSN: 1359-7108
DOI: 10.1049/ip-vis:20000307
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