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CSDC: a new complexity reduction technique for multiplierless implementation of digital FIR filters

机译:CSDC:一种新的降低复杂度的技术,用于数字FIR滤波器的无乘法器实现

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We present a computation reduction technique called computation sharing differential coefficient (CSDC) method, which can be used to obtain low-complexity multiplierless implementation of finite-impulse response (FIR) filters. It is also applicable to digital signal processing tasks involving multiplications with a set of constants. The main component of our proposed CSDC method is to combine the strength of the augmented differential coefficient approach and subexpression sharing. Exploring computation reuse through algorithmic equivalence, the augmented differential coefficient approach greatly expands the design space by employing both differences and sums of filter coefficients. The expanded design space is represented by an undirected and complete graph. The problem of minimizing the adder cost (the number of additions/subtractions) for a given filter is transformed into a problem of searching for an appropriate subexpression set that leads to a minimal adder cost. A heuristic search algorithm based on genetic algorithm is developed to search for low-complexity solutions over the expanded design space in conjunction with exploring subexpression sharing. It is shown that up to 70.1% reduction in the adder cost can be obtained over the conventional multiplierless implementation. Comparison with several existing techniques based on the available data shows that our method yields comparable results for multiplierless FIR filter implementation.
机译:我们提出了一种称为计算共享差分系数(CSDC)方法的计算简化技术,该技术可用于获得有限脉冲响应(FIR)滤波器的低复杂度无乘子实现。它也适用于涉及与一组常数相乘的数字信号处理任务。我们提出的CSDC方法的主要组成部分是将增强差分系数方法的强度与子表达式共享相结合。通过算法等效性探索计算重用,增强差分系数方法通过同时利用差分和滤波器系数之和来极大地扩展设计空间。扩展的设计空间由一个无向的完整图形表示。将给定滤波器的加法器成本(加法/减法数)最小化的问题被转化为寻找导致最小加法器成本的适当子表达式集的问题。开发了一种基于遗传算法的启发式搜索算法,在探索子表达式共享的同时,在扩展的设计空间中搜索低复杂度的解决方案。结果表明,与传统的无乘法器实现相比,可将加法器成本降低多达70.1%。与现有数据的几种现有技术的比较表明,对于无乘FIR滤波器的实现,我们的方法可获得可比的结果。

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