CMOS compatible building blocks for reservoir computing
This project was done to learn more about what a PRC is and to compare it against the traditional RNN models. Chaos maps are chosen to be the input due to their chaotic behaviour which serves as a great benchmark for our models. They also serve to test the model’s robustness to noise as well as thei...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/176881 |
| _version_ | 1824456990038949888 |
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| author | Wee, Jun Lin |
| author2 | Ang Diing Shenp |
| author_facet | Ang Diing Shenp Wee, Jun Lin |
| author_sort | Wee, Jun Lin |
| collection | NTU |
| description | This project was done to learn more about what a PRC is and to compare it against the traditional RNN models. Chaos maps are chosen to be the input due to their chaotic behaviour which serves as a great benchmark for our models. They also serve to test the model’s robustness to noise as well as their capability to process temporal and sequential data. In this project, Duffing Map, Gingerbreadman Map and Hénon Map are used as the testbench.
The PRC model and RNN model are pitted against each other in their capability to predict different chaos maps. By measuring the NRMSE value of the output respectively, this experiment proves to show whether a PRC model is much more efficient than a RNN model in using their computational resources. |
| first_indexed | 2025-02-19T04:02:52Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/176881 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T04:02:52Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1768812024-05-31T15:45:21Z CMOS compatible building blocks for reservoir computing Wee, Jun Lin Ang Diing Shenp School of Electrical and Electronic Engineering EDSAng@ntu.edu.sg Engineering This project was done to learn more about what a PRC is and to compare it against the traditional RNN models. Chaos maps are chosen to be the input due to their chaotic behaviour which serves as a great benchmark for our models. They also serve to test the model’s robustness to noise as well as their capability to process temporal and sequential data. In this project, Duffing Map, Gingerbreadman Map and Hénon Map are used as the testbench. The PRC model and RNN model are pitted against each other in their capability to predict different chaos maps. By measuring the NRMSE value of the output respectively, this experiment proves to show whether a PRC model is much more efficient than a RNN model in using their computational resources. Bachelor's degree 2024-05-31T00:02:41Z 2024-05-31T00:02:41Z 2024 Final Year Project (FYP) Wee, J. L. (2024). CMOS compatible building blocks for reservoir computing. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/176881 https://hdl.handle.net/10356/176881 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering Wee, Jun Lin CMOS compatible building blocks for reservoir computing |
| title | CMOS compatible building blocks for reservoir computing |
| title_full | CMOS compatible building blocks for reservoir computing |
| title_fullStr | CMOS compatible building blocks for reservoir computing |
| title_full_unstemmed | CMOS compatible building blocks for reservoir computing |
| title_short | CMOS compatible building blocks for reservoir computing |
| title_sort | cmos compatible building blocks for reservoir computing |
| topic | Engineering |
| url | https://hdl.handle.net/10356/176881 |
| work_keys_str_mv | AT weejunlin cmoscompatiblebuildingblocksforreservoircomputing |