Abstract
Problem statement: In order to improve and implement Fast Fourier Transform (FFT), in general, an efficient parallel form in digital signal processor is necessary. The butterfly structure is an important role in FFT, because its symmetry form is suitable for hardware implementation. Although it can perform a symmetric structure, the performance will be reduced under the data-dependent flow characteristic. Even though recent research which calls as Novel Memory Reference Reduction Methods (NMRRM) for FFT focus on reduce memory reference in twiddle factor, the data-dependent property still exists. Approach:In this study, we propose an approach for FFT implementation on DSP from analog device company (ADI) which is based on data-independent property and still hold the property of low-memory reference. We have applied the proposed method of radix-2 FFT algorithm in low-memory reference on ADI BlackFin561 DSP. Results: Experimental results show the method can reduce 44.36% clock cycles comparing with the NMRRM FFT implementation and keep the low-memory reference property. Conclusions/Recommendations: From our algorithm, the results can be accepted and realized for DSP-based embedded system. In further, we will try to implement on different DSP-based system in order to improve the algorithm values.
Highlights
The signal processing plays an important role for audio coding, image compression and video processing in real application
The experimental results show that our approach has lower clock cycles than Novel Memory Reference Reduction Methods (NMRRM) Fast Fourier Transform (FFT) in radix-2 DIF FFT and average of 44.36% reduction in the number of clock cycles, in addition, the approach keep low-memory reference property
The performance still equals to NMRRM FFT on radix-2 model which has better performance than analog device company (ADI)’s library
Summary
The signal processing plays an important role for audio coding, image compression and video processing in real application. Data domain transformation is an essential step for above application. The discrete Fourier transform (DFT) is main and important procedure in the data analysis, system design and implementation[1]. The DFT formula can be expressed by: includes the higher radix FFT[2], the mixed-radix FFT[3], the prime-factor FFT[4], the recursive FFT[5] and lowmemory reference FFT[6]. One is applicationspecific integrated circuits (ASIC) system such as[7,8]. The ASIC-based system can fit real application for lowpower or high performance; it is very hard to modify the function.
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