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SQNR improvement in fixed-point FFT architecture

机译:固定点FFT架构的SQNR改进

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摘要

In Digital Signal Processing (DSP), Fast Fourier Transform (FFT) algorithm and its hardware implementation play a significant role. To implement FFT in hardware, fixed point arithmetic is preferred as it is simple to execute and also saves area and power. The finite bit representation of signals and coefficients in fixed point result in quantization error which degrades FFT performance mainly Signal to Quantization Noise Ratio (SQNR). In this paper, SQNR improvement in fixed-point FFT is achieved by modifying Radix-2 Decimation In Time (DIT) conventional butterfly structure.
机译:在数字信号处理(DSP)中,快速傅里叶变换(FFT)算法及其硬件实现发挥了重要作用。为了实现硬件中的FFT,优选的固定点算法是易于执行的,并且还可以节省区域和电源。固定点中信号和系数的有限位表示导致量化误差,其将FFT性能提升到量化噪声比(SQNR)。在本文中,通过在时间(DIT)常规蝶形结构中改变基数-2抽取来实现定点FFT的SQNR改进。

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