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| Home > External Publications > Vita Publications > Implementation of a Spiking Neural Network Model with Biologically Plausible Connectivity Characteristics for Neuromorphic Benchmarking > print |
| Home > External Publications > Vita Publications > Implementation of a Spiking Neural Network Model with Biologically Plausible Connectivity Characteristics for Neuromorphic Benchmarking > print |
| 001 | 943468 | ||
| 005 | 20230203120221.0 | ||
| 037 | _ | _ | |a FZJ-2023-01037 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Kempter, Miriam |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Implementation of a Spiking Neural Network Model with Biologically Plausible Connectivity Characteristics for Neuromorphic Benchmarking |f - 2022-11-08 |
| 260 | _ | _ | |c 2022 |
| 300 | _ | _ | |a 65 p. |
| 336 | 7 | _ | |a bachelorThesis |2 DRIVER |
| 336 | 7 | _ | |a Thesis |0 2 |2 EndNote |
| 336 | 7 | _ | |a Output Types/Supervised Student Publication |2 DataCite |
| 336 | 7 | _ | |a Bachelor Thesis |b bachelor |m bachelor |0 PUB:(DE-HGF)2 |s 1675339424_26081 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a MASTERSTHESIS |2 BibTeX |
| 336 | 7 | _ | |a SUPERVISED_STUDENT_PUBLICATION |2 ORCID |
| 502 | _ | _ | |a Bachelorarbeit, RWTH Aachen, 2022 |c RWTH Aachen |b Bachelorarbeit |d 2022 |
| 520 | _ | _ | |a The cortex exhibits a complex connectivity structure, containing spatially clustered connectivity patterns. Those, so-called patchy connections, are often neglected in studies concerning neural networks. However, they perform an important role in the efficiency of the cortex. The goal of neuromorphic hardware systems is, to imitate the highly efficient cortex structure, and perform faster-than-realtime calculations. In order to benchmark the performance of such systems, it is important to have realistic neural network models available. Here, such a benchmark model will be presented. Focusing on connectivity, the restrains on all other network aspects are kept to a minimum. It respects the biological distant dependent connectivity patterns, including spatial structure and patchy connectivity. Three different variations of the model, with slightly different spatially clustering approaches, are constructed. Additionally the model will provide benchmarking features. A fourth model, without spatial clustering is included to serve as a comparison. |
| 536 | _ | _ | |a ACA - Advanced Computing Architectures (SO-092) |0 G:(DE-HGF)SO-092 |c SO-092 |x 0 |
| 536 | _ | _ | |a SLNS - SimLab Neuroscience (Helmholtz-SLNS) |0 G:(DE-Juel1)Helmholtz-SLNS |c Helmholtz-SLNS |x 1 |
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| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/943468/files/BachelorThesis.pdf |y Restricted |
| 909 | C | O | |o oai:juser.fz-juelich.de:943468 |p extern4vita |
| 910 | 1 | _ | |a RWTH Aachen |0 I:(DE-588b)36225-6 |k RWTH |b 0 |6 P:(DE-HGF)0 |
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| 920 | _ | _ | |l yes |
| 980 | 1 | _ | |a EXTERN4VITA |
| 980 | _ | _ | |a bachelor |
| 980 | _ | _ | |a EDITORS |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
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