Cellular automata pseudorandom sequence generation
| dc.contributor.author | Acharya, Smarak | |
| dc.contributor.supervisor | Gulliver, T. Aaron | |
| dc.date.accessioned | 2017-08-25T14:31:08Z | |
| dc.date.available | 2017-08-25T14:31:08Z | |
| dc.date.copyright | 2017 | en_US |
| dc.date.issued | 2017-08-25 | |
| dc.degree.department | Department of Electrical and Computer Engineering | |
| dc.degree.level | Master of Applied Science M.A.Sc. | en_US |
| dc.description.abstract | Pseudorandom sequences have many applications in fields such as wireless communication, cryptography and built-in self test of integrated circuits. Maximal length sequences (m-sequences) are commonly employed pseudorandom sequences because they have ideal randomness properties like balance, run and autocorrelation. However, the linear complexity of m-sequences is poor. This thesis considers the use of one-dimensional Cellular Automata (CA) to generate pseudorandom sequences that have high linear complexity and good randomness. The properties of these sequences are compared with those of the corresponding m-sequences to determine their suitability. | en_US |
| dc.description.scholarlevel | Graduate | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/8455 | |
| dc.language | English | eng |
| dc.language.iso | en | en_US |
| dc.rights | Available to the World Wide Web | en_US |
| dc.subject | Cellular Automata | en_US |
| dc.subject | Pseudorandom | en_US |
| dc.subject | m-sequence | en_US |
| dc.subject | Linear Complexity | en_US |
| dc.subject | Randomness | en_US |
| dc.subject | Balance | en_US |
| dc.subject | Run | en_US |
| dc.subject | Autocorrelation | en_US |
| dc.subject | 1D CA Evaluation System | en_US |
| dc.title | Cellular automata pseudorandom sequence generation | en_US |
| dc.type | Thesis | en_US |