Design perfect reconstruction cosine-modulated filter banks via quadratically constrained quadratic programming and least squares optimization
•Formulate PR CMFB design as a QCQP with variables in special re-arrangement.•Dig out the algebraic relationship between PR conditions and NPR ones.•Propose an efficient two-stage method for PR CMFB design. In this paper, the design of perfect reconstruction (PR) cosine-modulated filter banks (CMFBs...
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| Vydáno v: | Signal processing Ročník 141; s. 199 - 203 |
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| Jazyk: | angličtina |
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Elsevier B.V
01.12.2017
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| ISSN: | 0165-1684, 1872-7557 |
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| Abstract | •Formulate PR CMFB design as a QCQP with variables in special re-arrangement.•Dig out the algebraic relationship between PR conditions and NPR ones.•Propose an efficient two-stage method for PR CMFB design.
In this paper, the design of perfect reconstruction (PR) cosine-modulated filter banks (CMFBs) is implemented via quadratically constrained quadratic programming (QCQP) and least squares (LS) optimization. To this end, a PR CMFB design problem is formulated as a nonconvex QCQP after re-arranging the coefficients of the prototype filter. Then a deep insight is offered into the algebraic relationship between the PR conditions and near-perfect reconstruction (NPR) ones for CMFB designs. Here we theoretically show that the NPR conditions are just the summations of the PR conditions. Firmly in the light of this relationship, a two-stage method is proposed for PR CMFB design. We firstly solve an NPR CMFB problem to obtain its optimal solution as a reference point, then model the PR CMFB design problem as a series of small-sized LS problems near the reference point. And we solve the LS problems in parallel with cheap iteration. Our analysis and numerical results show that the proposed method bears superior performance on effectiveness and efficiency, especially in the case of designing PR CMFBs with large number of channels. |
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| AbstractList | •Formulate PR CMFB design as a QCQP with variables in special re-arrangement.•Dig out the algebraic relationship between PR conditions and NPR ones.•Propose an efficient two-stage method for PR CMFB design.
In this paper, the design of perfect reconstruction (PR) cosine-modulated filter banks (CMFBs) is implemented via quadratically constrained quadratic programming (QCQP) and least squares (LS) optimization. To this end, a PR CMFB design problem is formulated as a nonconvex QCQP after re-arranging the coefficients of the prototype filter. Then a deep insight is offered into the algebraic relationship between the PR conditions and near-perfect reconstruction (NPR) ones for CMFB designs. Here we theoretically show that the NPR conditions are just the summations of the PR conditions. Firmly in the light of this relationship, a two-stage method is proposed for PR CMFB design. We firstly solve an NPR CMFB problem to obtain its optimal solution as a reference point, then model the PR CMFB design problem as a series of small-sized LS problems near the reference point. And we solve the LS problems in parallel with cheap iteration. Our analysis and numerical results show that the proposed method bears superior performance on effectiveness and efficiency, especially in the case of designing PR CMFBs with large number of channels. |
| Author | Yang, Zhiming Liu, Hongying Yi, Caixia |
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| Keywords | Near-perfect reconstruction Quadratically constrained quadratic programming Perfect reconstruction Least squares Cosine-modulated filter bank |
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| SubjectTerms | Cosine-modulated filter bank Least squares Near-perfect reconstruction Perfect reconstruction Quadratically constrained quadratic programming |
| Title | Design perfect reconstruction cosine-modulated filter banks via quadratically constrained quadratic programming and least squares optimization |
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