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The Fast Fourier Transforms for Technologists, Engineers, and Other Non-Ph.D.s

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Conference

2012 ASEE Annual Conference & Exposition

Location

San Antonio, Texas

Publication Date

June 10, 2012

Start Date

June 10, 2012

End Date

June 13, 2012

ISSN

2153-5965

Conference Session

Engineering Technology Curriculum Innovations

Tagged Division

Engineering Technology

Page Count

21

Page Numbers

25.1297.1 - 25.1297.21

DOI

10.18260/1-2--22054

Permanent URL

https://peer.asee.org/22054

Download Count

581

Paper Authors

biography

William H. Blanton East Tennessee State University

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William Blanton has taught in the Engineering Technology Department at East Tennessee State University for 12 years. He is coordinator of the biomedical engineering technology concentration. His teaching interests are medical imaging and digital signal processing.

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biography

Zhibin Tan East Tennessee State University

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Department of Engineering Technology, Surveying, and Digital Media

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Davin A. Strom East Tennessee State University

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Abstract

The Fast Fourier Transforms for Technologists, Engineers, and Other Non-Ph.D.s William H. Blanton & Zhibin TanABSTRACT.The number of professional areas that Fourier transforms appear is impressive. Fouriertransforms play an important role in optics, medical imaging, acoustics, waveform analysis, andeven business analysis. Quite often the Fourier Transform is first encountered in a formalmathematics class as an afterthought to the study of the Fourier series. As needed, the Fouriertransform is revisited in senior level and graduate level courses. The relevancy of the Fouriertransform to many professional areas strongly qualifies the subject for introduction at an earlystage in one’s academic career. A good introduction to the Fourier transform is the fast Fouriertransform (FFT). The FFT is an efficient algorithm based on the discrete Fourier transform(DFT) for converting time domain sequences into frequency domain sequences. The resultsobtained by the FFT are exactly the same results that obtained by the DFT, not an approximationof the DFT. Whereas the evaluation of an N-point DFT requires N2 complex multiplications andadditions, the FFT method (assuming N is power of 2) requires N log2 N operations. Theinclusion of the FFT in the MATLAB function set provides a good entry point for the study ofthe Fourier transform by technologists, engineers, and other non-Ph.D.s.

Blanton, W. H., & Tan, Z., & Strom, D. A. (2012, June), The Fast Fourier Transforms for Technologists, Engineers, and Other Non-Ph.D.s Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. 10.18260/1-2--22054

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