Optimization of the Quantized Coefficients for DDFS Utilizing Polynomial Interpolation Methods

IEEE Transactions on Circuits and Systems Ii-express Briefs(2014)

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摘要
In this brief, a novel method to find the optimized quantized coefficients for direct digital frequency synthesizers (DDFSs) based on polynomial interpolation methods is introduced. First, a new method is introduced to find the spurious-free dynamic-range upperbound for DDFSs with a polynomial interpolation method, utilizing the discrete Fourier transform and the Chebyshev minimax problem. This method can be modified to obtain quantized coefficients by employing mixed-integer linear programming. In this problem, the polynomial coefficients are presented in a positive sum of powers of two (SPT) and unsigned integer forms. The proposed method is used to design the linear interpolation-based DDFSs with nonuniform segmentations. The VLSI realizations of the designs with nonuniform segmentations are provided, where it is shown that they have a smaller silicon area and higher clock frequencies compared with the state-of-the-art designs reported in literature.
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关键词
positive sum of powers of two,optimized quantized coefficients,spurious free dynamic range upperbound,chebyshev minimax problem,interpolation,unsigned integer forms,integer programming,polynomial interpolation,convex programming,polynomial coefficients,discrete fourier transform,linear programming,polynomial approximation,direct digital frequency synthesizers,discrete fourier transforms,mixed integer linear programming,vlsi,linear interpolation,spurious-free dynamic range (sfdr),direct digital synthesis,direct digital frequency synthesizers (ddfss),convex optimization,mixed-integer linear programming (milp),ddfs,polynomial interpolation methods
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