Name
Title | ||
|---|---|---|
Towards More Realistic Self Contained Models of Neurons: High-Order, Recurrence and Local Learning |
Abstract | ||
|---|---|---|
The anatomy and physiology of biological neurons is revisited looking at a minimum set of computational requirements to be included in new and more complex models of self-contained local computation ANN. Some of these functionalities are then integrated and the corresponding model is evaluated. Properties included are: (1) locality and autonomy in all the computations including the learning algorithms. (2) a layered architecture with high-order recurrent neurons, (3) self and external programming via input spaces and (4) fault tolerance after physical lesion, or even elimination of one or more neurons. |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1007/3-540-56798-4_124 | IWANN |
Keywords | Field | DocType |
realistic self contained models,self-contained models,local learning,input programming,fault tolerance.,recurrent neurons,layered architecture,fault tolerant | Locality,Local learning,Computer science,Theoretical computer science,Fault tolerance,Artificial intelligence,Machine learning,Multitier architecture,Computation | Conference |
ISBN | Citations | PageRank |
3-540-56798-4 | 11 | 1.66 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Mira | 1 | 543 | 71.44 |
| Ana E. Delgado García | 2 | 87 | 10.85 |
| José R. Álvarez | 3 | 487 | 59.45 |
| A. P. de Madrid | 4 | 15 | 2.95 |
| Matilde Santos | 5 | 143 | 24.39 |