True pseudo-random number generation using chaotic maps
In this paper, a new algorithm for generating True Pseudo-Random Number Generator (TPRNG) is proposed. This TPRNG uses chaos theory in dynamic systems that are highly sensitive to changes in initial conditions. The proposed algorithm uses a modified version of the logistic map to generate large sequ...
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| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2015
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| Online Access: | http://hdl.handle.net/10356/65200 |
| _version_ | 1811680487910932480 |
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| author | Chong, Wei Zhen |
| author2 | Lin Rongming |
| author_facet | Lin Rongming Chong, Wei Zhen |
| author_sort | Chong, Wei Zhen |
| collection | NTU |
| description | In this paper, a new algorithm for generating True Pseudo-Random Number Generator (TPRNG) is proposed. This TPRNG uses chaos theory in dynamic systems that are highly sensitive to changes in initial conditions. The proposed algorithm uses a modified version of the logistic map to generate large sequence of pseudo-random numbers. The performance of the TPRNG is evaluated through exploratory data analysis and several statistical tests from the DIEHARD test suite. The results were promising as they suggest that the numbers have a good distribution and are highly random and independent for a wide range of parameters. Further tests were conducted to compare the TPNG against other existing generators. The analysis showed that the TPRNG is truly more random than common generators used. It can be concluded that the TPRNG can generate a large amount of usable random numbers that are suitable for simulations and other scientific computing applications.
Further improvements and recommendations were discussed as well. |
| first_indexed | 2024-10-01T03:25:50Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/65200 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:25:50Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | ntu-10356/652002023-03-04T19:26:04Z True pseudo-random number generation using chaotic maps Chong, Wei Zhen Lin Rongming School of Mechanical and Aerospace Engineering DRNTU::Engineering::Aeronautical engineering In this paper, a new algorithm for generating True Pseudo-Random Number Generator (TPRNG) is proposed. This TPRNG uses chaos theory in dynamic systems that are highly sensitive to changes in initial conditions. The proposed algorithm uses a modified version of the logistic map to generate large sequence of pseudo-random numbers. The performance of the TPRNG is evaluated through exploratory data analysis and several statistical tests from the DIEHARD test suite. The results were promising as they suggest that the numbers have a good distribution and are highly random and independent for a wide range of parameters. Further tests were conducted to compare the TPNG against other existing generators. The analysis showed that the TPRNG is truly more random than common generators used. It can be concluded that the TPRNG can generate a large amount of usable random numbers that are suitable for simulations and other scientific computing applications. Further improvements and recommendations were discussed as well. Bachelor of Engineering (Aerospace Engineering) 2015-06-15T08:26:00Z 2015-06-15T08:26:00Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/65200 en Nanyang Technological University 55 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Aeronautical engineering Chong, Wei Zhen True pseudo-random number generation using chaotic maps |
| title | True pseudo-random number generation using chaotic maps |
| title_full | True pseudo-random number generation using chaotic maps |
| title_fullStr | True pseudo-random number generation using chaotic maps |
| title_full_unstemmed | True pseudo-random number generation using chaotic maps |
| title_short | True pseudo-random number generation using chaotic maps |
| title_sort | true pseudo random number generation using chaotic maps |
| topic | DRNTU::Engineering::Aeronautical engineering |
| url | http://hdl.handle.net/10356/65200 |
| work_keys_str_mv | AT chongweizhen truepseudorandomnumbergenerationusingchaoticmaps |