Volume 5, Issue 4, July 2017, Pages: 29-50
Received: Dec. 21, 2017;
Accepted: Jan. 4, 2018;
Published: Jan. 31, 2018
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Amannah Constance Izuchukwu, Department of Computer Science, University of Nigeria, Nsukka, Nigeria
H. C. Inyiama, Department of Computer Science, University of Nigeria, Nsukka, Nigeria
This research was designed to develop an extended improvement on the simplified Bluestein algorithm (EISBA). The methodology adopted in this work was iterative and incremental development design. The major technologies used in this work are the numerical algorithms and the C++ programming technologies and the wave concept technology. The C++ served as a signal processing language simulator (SPLS). In the EISBA, the DSP input is encountered first. It is subjected to some numerical processing which included testing for efficiency on the C++ platform. This test platform provided the basis for comparison leading to the desired EISBA. The approach adopted in the study was the re-indexing, decomposing, and simplifying the default SBFFT algorithm. The computing speed of the default algorithms was tested on the C++ platform. The average execution time of the SBFFT was 3.50 seconds. Similarly, the average execution time of the EISBA was 1.74 ms. this result therefore shows that a version of algorithm with computing speed that is faster than that of SBFFT algorithm exist. The algorithms were tested on input block of width 1000 units, and above, and can be implemented on input size of 100 000, and 1000 000 000 without the challenge of storage overflow. The input samples tested in this work was the discretized pulse wave form with undulating shape out of which the binary equivalents were extracted. Other forms of signals may also be tested in the EISBA provided they are interpreted in the digital wave type.
Amannah Constance Izuchukwu,
H. C. Inyiama,
Development of an Extended Improvement on the Simplified-Bluestein Algorithm, Communications.
Vol. 5, No. 4,
2017, pp. 29-50.
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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