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首页> 外文期刊>International Journal of Knowledge-Based in Intelligent Engineering Systems >An economical modified VLSI architecture for computing power spectral density supported welch method
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An economical modified VLSI architecture for computing power spectral density supported welch method

机译:一种经济的改进的VLSI架构,用于计算功率谱密度支持的Welch方法

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The Welch algorithm furnishes a good estimate of the spectral power at the expense of high computational complexity. The primary intension is to compute the FFT of the individual non-overlapped parts (i.e., half of the original segments) and acquire the FFT of the overlapped segments by merging those of the non-overlapped segments. In this paper, initially the input discrete signal is subjected to an L/2-point FFT and then the two successive segments are merged to L-point segment using a modified architecture utilizing an improved Fractional Delay Filter(FDF) design by adapting a Multiplier less implementation for efficient contribution. The merged segments are then subjected to a window filter, designed using delay lines and shifters replacing the multiplier blocks. Finally the power spectral density (PSD) is computed by computing the periodogram and then averaging the periodogram for the windowed segments. Complete module is realized using Xilinx_ISE software with the target device as xc4vfx100-12-ff1152. The design is coded in verilog HDL. The functional verification of the proposed design reported a PSD with an error of 5.87% when compared with the similar Matlab PSD computation. The synthesis results confirm the efficiency and computational complexity reduction of the proposed architecture when comparing with similar existing researches.
机译:韦尔奇算法以高计算复杂度为代价,很好地估计了频谱功率。主要意图是计算各个非重叠部分(即原始段的一半)的FFT,并通过合并非重叠部分的FFT获得重叠段的FFT。在本文中,首先对输入的离散信号进行L / 2点FFT,然后使用经过改进的分数阶延迟滤波器(FDF)设计,通过改编乘数,使用改进的体系结构,将两个连续的段合并为L点段减少执行工作以实现有效的贡献。合并的段然后经过窗口滤波器,使用延迟线和移位器代替乘法器块进行设计。最后,通过计算周期图,然后对窗口段的周期图求平均值,可以计算出功率谱密度(PSD)。使用Xilinx_ISE软件将目标设备作为xc4vfx100-12-ff1152来实现完整的模块。该设计以Verilog HDL编码。与类似的Matlab PSD计算相比,所提出设计的功能验证报告了PSD的误差为5.87%。与类似的现有研究相比,综合结果证实了所提出体系结构的效率和计算复杂度的降低。

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