Published March 2, 2022
                      
                       | Version v1
                    
                    
                      
                        
                          Dataset
                        
                      
                      
                        
                          
                        
                        
                          Open
                        
                      
                    
                  Connectome of memristive nanowire networks through graph theory - Dataset
- 1. Istituto Nazionale di Ricerca Metrologica (INRiM)
- 2. Universitat Autònoma de Barcelona (UAB)
- 3. Politecnico di Torino
Description
This is the dataset of "Connectome of memristive nanowire networks through graph theory"
Notes
Files
      
        Figure 2d - Degree of nodes distribution 300 NWs.txt
        
      
    
    
      
        Files
         (245.0 kB)
        
      
    
    | Name | Size | Download all | 
|---|---|---|
| md5:a93c59d60b774d551698feec41196dd3 | 320 Bytes | Preview Download | 
| md5:3b8d6c4c6fcda8f7af3c75502f4937e8 | 660 Bytes | Preview Download | 
| md5:9f453ccaffd5c057ac93167d89b45812 | 679 Bytes | Preview Download | 
| md5:51cb7fc09d1f82da698f222c24239a36 | 2.2 kB | Preview Download | 
| md5:69dac9d922213aa3687559b54fc66a09 | 51.0 kB | Preview Download | 
| md5:879783145515e4bb98f91b3c2d964dc1 | 706 Bytes | Preview Download | 
| md5:26152962f73c7dd9c1e0df7a2fbee621 | 702 Bytes | Preview Download | 
| md5:fdba4a2f7d0614dc892e0a8045cf6af9 | 262 Bytes | Preview Download | 
| md5:c499d8ec85cde3b642137020a7ac576d | 509 Bytes | Preview Download | 
| md5:8eee9a3ca2ad9c1bfd69b5b7a9038e4e | 470 Bytes | Preview Download | 
| md5:e44564bbfc8e5c81e875890c0481dc80 | 599 Bytes | Preview Download | 
| md5:0f8fad4b44556355f76300d210ceaef3 | 317 Bytes | Preview Download | 
| md5:7263c9c22c92905c1ddaf63596a16ba0 | 608 Bytes | Preview Download | 
| md5:3b1b1c84fffeaa748fa9671f9eb6b4ad | 950 Bytes | Preview Download | 
| md5:b902eff4a10b6e6efc20453f939aa8ae | 456 Bytes | Preview Download | 
| md5:1042b28c0e6614d735af2181d6a024d0 | 30.7 kB | Preview Download | 
| md5:48c0c7d70685134b555a4a0fe917505a | 97.6 kB | Preview Download | 
| md5:d95b87fce835771d93bbcdc562039f01 | 53.7 kB | Preview Download | 
| md5:59500621f6d6eff3a58b57930e6055ae | 2.6 kB | Preview Download | 
Additional details
Related works
- Is cited by
- Journal article: 10.1016/j.neunet.2022.02.022 (DOI)