The paper proposes the design of linear phase filters using the optimization techniques based on methods for sparse signal restoration. The filter response is treated as weighted sum of the phase shifted versions of the signal. The filter design problem is converted into form Ax ≈ b, where A has rows given by [1 cos(-ω) cos(-2ω...) ], corresponding to a given frequency ω. x corresponds to the filter coefficients and b = R(ω) cos φ(ω), where R stands for the magnitude and φ the phase of the desired response. The problem is formulated into an L1 term and and L2 term and solved iteratively using ISTA (Iterative Soft Thresholding Algorithm ) to get the filter coefficients. The visible outcome of the approach is the considerable reduction in the non-zero coefficients. © 2011 IEEE.
cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@4e2708e ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@2e4b7d23 Through org.apache.xalan.xsltc.dom.DOMAdapter@5e049c93; Conference Code:87395
K. Lakshmi and Soman, K. P., “Filter design using sparse signal restoration techniques”, in 2011 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2011, Trivandrum, Kerala, 2011, pp. 396-400.