{"title":"Least p/sup th/ power design of complex FIR 2-D filters using the complex Newton method","authors":"T. Abatzoglou, A. Jaffer","doi":"10.1109/ICASSP.1995.480473","DOIUrl":null,"url":null,"abstract":"A design of 2-D complex FIR filters is proposed by minimizing the p/sup th/ power norm used to measure the deviation of the FIR filter response from a desired filter response. The solution of this problem cannot be obtained in closed form except for p=2; for arbitrary p>2 the authors present an approach which treats the problem from a complex variable point of view. An iterative scheme is described based on the complex Newton method to find the solution. It has the feature that, starting with p=2, the value of p is increased after each iteration. Because the objective function is convex any local extremum is the global minimum. Convergence can be attained after a moderate number of iterations. A characterization theorem for factorization of 2-D FIR filters in terms of 1D filters is derived. This has strong implications for large order 2-D filter design. Two filter design examples are included.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1995 International Conference on Acoustics, Speech, and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.1995.480473","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
A design of 2-D complex FIR filters is proposed by minimizing the p/sup th/ power norm used to measure the deviation of the FIR filter response from a desired filter response. The solution of this problem cannot be obtained in closed form except for p=2; for arbitrary p>2 the authors present an approach which treats the problem from a complex variable point of view. An iterative scheme is described based on the complex Newton method to find the solution. It has the feature that, starting with p=2, the value of p is increased after each iteration. Because the objective function is convex any local extremum is the global minimum. Convergence can be attained after a moderate number of iterations. A characterization theorem for factorization of 2-D FIR filters in terms of 1D filters is derived. This has strong implications for large order 2-D filter design. Two filter design examples are included.