Theories And Algorithms For Fast Designs Of Twodimensional Constrained FIR Filters  Posted on:20160113  Degree:Doctor  Type:Dissertation  Country:China  Candidate:X Y Hong  Full Text:PDF  GTID:1108330461984434  Subject:Signal and Information Processing  Abstract/Summary:  Request the fulltext of this thesis  With the rapid development of computer technology in storage capabilities and speed, twodimensionl (2D) digital filter has found more and more applications in areas such as medical image processing, satellite image processing, and radar and sonar signal processing, and the design problem of it has received considerable attention by many scholars at home and abroad.2D digital filter can be classified into 2D finite impulse response (FIR) fiter and infinite impulse response (IIR) filter. FIR filters are often preferable to IIR ones since they are inherently stable and can be designed easily to have exact linear phase responses.High computation complexity is the major difficult in the design of 2D fiters. The impluse coefficients of 2D digital filter are naturally arranged in matrices, which are different from that in one dimensional (1D) filter, thus the design of 2D fiter is actually the approximaton problem of bivariate funciton. Incompleteness of the approximation theory of bivariate funciton leads to the complexity of design problem. Conventional design methods for optimal designs of 2D FIR filters rearrange the coefficient matrices into vectors and then solve the design problem using algorithms for 1D FIR filters. This leads to high computational complexities of the design algorithms and much design time. There are also several works that formulate the design problem in term of the coefficient matices and delevop algorithms to directly solve for the coefficient matrices rather than vectorizing them first, leading to lower computational complexities than corresponding algorithms vectorizing the coefficient matrices. For simplicity, we refer to the algorithms that directly solve for the coefficient matrices as matrixbased algorithms, and those vectorizing the coefficent matrices as vectorized algorithms. The exist matrixbased algorithms only consider (weight) leastsquares designs of 2D FIR filters without any other constraints, that restricts the wide application of algorithms.For fast design problems of 2D FIR filters, this paper first considers explicit constraints in matrixbased algorithms and proposes fast design algorithms to solve the constrained leastsquares (CLS) and (constrained) minimax design problems, which overcomes the difficulties that existing matrixbased algorithms cannot design 2D constrained FIR filters.The author in [70] has pointed that quadrantally symmetric filter is a special case in centro symmetirc filter that is symmetric about two axes, and centro symmetirc filter is a special case in conjugate symmetric complex filer with real impluse respones coefficients, and quadrantally symmetric, centro symmetirc and conjugate symmetric complex filers all belong to linearphase 2D FIR filter. Obviously, the linear 2D FIR filter is also special case in 2D FIR filters with arbitrarily magnitude and phase response. Thus, according to the progressive principle, we will study in turn the matrixbased CLS design and minimax design problems of 2D FIR filtes with quadrantally symmetric, centro symmetric, conjugate symmetric complex and arbitrarily specified frequency response, and propose matrixbased theories and algorithms.The major work is as follows:(1) Consider the CLS design and minimax design problem of quadrantally symmetric 2D FIR filtes. The CLS design of quadrantally symmetric 2D FIR filtes can be directly transformed into a convex quadratic programming (OP) problem with only one real coefficient matrix. Three matrixbased CLS algorithms I, II, III have been proposed to solve such problem. Design examples and comparisons with the existing method demostrate that, three matrixbased CLS algorithms are all effecitve and efficient than existing methos when given magnitude error constraints are not tight, and the matrixbased CLS algorithms I has convergence problem when given magnitude error constraints are very tight (near the minimax solution). The matrixbased CLS algorithms III is the most efficient one for the designs of high order filters. The matrixbased SCLS and mixed L2/L∞ methods are proposed to transform the matrixbased minimax design problem into the same form with the matrixbased CLS design to solve. Design examples and comparisons with several existing algorithms demonstrate the effectiveness and efficiency of the proposed algorithms.(2) The CLS design and minimax design problems of centro symmetric 2D FIR filtes are considered. The CLS design of centro symmetric 2D FIR filtes can be expressed as a convex OP problem with real two coefficient matrices. Thinking of the convergence, the paper only extend the matrix CLS algorithms II and III to this case. The matrixbased SCLS and mixed L2 /L∞ methods are extended to transform the matrixbased minimax design problem into a convex OP problem with two real coefficient matrices to solve. Design examples illustrate that these algorithms are very efficient.(3) Consider the CLS design and minimax design problems of conjugate symmetric complex 2D FIR filtes. The matrixbased CLS design and minimax design can both be transform into the matrixbased convex OP problem with four real coefficient matrices directly or indirectly after equivalently conversion by matrixbased mixed L2/L∞ method. Only the matrixbased CLS algorithm III is extended to the optimal design problem of this kind of filter on base of convergence and efficiency.(4) The CLS design and (constrained) minimax design problems of 2D FIR filters with arbitrarily magnitued and phase responses are studied. The ellipticerror and phaseerror constrained optimal design model is proposed. The CLS design with ellipticerror and phaseerror constraints (EPCLS), the minimax ellipticerror magnitude design with phaseerror constraints (PMMEE), the minimax phase error design with ellipticerror magnitude constraints (EMMPE) and the minimax phase error design with minmizing the maximum of complexerror magnitude simultaneously (MMPEEE) can all be directly or indirectly (i.e. by extending the matrixbased mixed L2/L∞ or SCLS method) transformed into the matrixbased semiinfinite convex QP problem with only one coefficient matrix. The matrixbased EPCLSGI algorithm is proposed to solve such problem by combing the matrixbased CLS algorithms Ⅲ with existing vectorized CPCLSGI algorithm [24], which reduces the computation complexity from O(N6) to O(N4) and greatly improves the computational efficiency of the algorithm. A filter type dependent 2D Sigmoid phaseerror upperbound function is introduced to reduce the maximum group delay error. The optimal design model of CIS and minimax design with ellipticerror constraints and 2D Sigmoid phaseerror upperbound function can reduce the maximum groupdelay error greatly and reduce the magnitude error effectively. Design examples and comparisions with existing methods illustrate the effectiveness and high efficiency of the proposed methods.All algorithms proposed in this dissertation are the matrixbased algorithms, i.e., the design procedure always keep the coefficient nature matrix form. Large numbers of design examples indicate that they are computationally high efficient, and can be design various 2D FIR filters.  Keywords/Search Tags:  twodimensional FIR filter, constrained leastsquare design, minimax design, matrixbased algorithm, elliptic complexerror, twodimensional Sigmoid phaseerror upper function  Request the fulltext of this thesis  Related items 
 
