1999
DOI: 10.1016/s0165-1684(99)00098-5
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Real-time implementation of the moving FFT algorithm

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Cited by 14 publications
(5 citation statements)
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“…The algorithm can be implemented as a standalone spectral analyzer board at a price of approximately $500 plus the cost of the display unit, without the need to interface with a computer. Although it is possible to improve the efficiency of the DFT real-time update and the compiler by as much as 20 × [ 1 , 2 ], such implementations would not match the improvement gained by using the NSE real-time algorithm, which was found by comparison of software algorithms to be approximately 150 × faster. The sampling rate using the hardware implementation of the NSE could possibly be further increased, being limited only by the settling times of the on-board components as compared with the fast clock speed.…”
Section: Discussionmentioning
confidence: 99%
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“…The algorithm can be implemented as a standalone spectral analyzer board at a price of approximately $500 plus the cost of the display unit, without the need to interface with a computer. Although it is possible to improve the efficiency of the DFT real-time update and the compiler by as much as 20 × [ 1 , 2 ], such implementations would not match the improvement gained by using the NSE real-time algorithm, which was found by comparison of software algorithms to be approximately 150 × faster. The sampling rate using the hardware implementation of the NSE could possibly be further increased, being limited only by the settling times of the on-board components as compared with the fast clock speed.…”
Section: Discussionmentioning
confidence: 99%
“…The radix-2 FFT program was also implemented for real time [ 16 ]. For ease of comparison, all FFT calculations were repeated for each sliding analysis window rather than using any of the shortcuts suggested by other authors [ 1 , 2 ]. Because the repetition of FFT calculations is time-consuming, it was run for only 512 input sample points.…”
Section: Methodsmentioning
confidence: 99%
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“…The absolute phase of these two signals could be measured using a moving or sliding FFT (Ref. 33) and compared as shown in Fig. 8.…”
Section: Coherent Scatteringmentioning
confidence: 99%
“…In many technical branches, Fast Fourier Transform (FFT) is used to compute discrete Fourier transform and to get the frequency characteristic of a signal [10], [11]. When only a signal power at selected frequencies is needed, the Running Discrete Fourier Transform (RDFT) is more effective [12].…”
Section: Introductionmentioning
confidence: 99%