| dc.contributor |
Pujol Vila, Oriol |
|
| dc.creator |
Navarro i López, Andrea |
|
| dc.date |
2016-05-04T09:09:48Z |
|
| dc.date |
2016-05-04T09:09:48Z |
|
| dc.date |
2016-01-22 |
|
| dc.date.accessioned |
2024-12-16T10:22:27Z |
|
| dc.date.available |
2024-12-16T10:22:27Z |
|
| dc.identifier |
http://hdl.handle.net/2445/98246 |
|
| dc.identifier.uri |
http://fima-docencia.ub.edu:8080/xmlui/handle/123456789/14354 |
|
| dc.description |
Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2016, Director: Oriol Pujol Vila |
|
| dc.description |
One of the main features of the living beings, in special the human, is the capacity of learning. And the fact is that the great dream of the artificial intelligence is to achieve the creation of machines as intelligent as any one of us. Even still being away from succeeding, many researchers in the matter think that the best way to achieve it is from algorithms of learning, that test to imitate how the human brain works. The artificial neural networks simulate the behaviour of the biological nervous system. It treats of a system of models of artificial neurons, interconnected, arranged in a network with the purpose to collaborate to attain their common aim: the learning. In spite of the differences of structure between the biological and the artificial system, in both cases we find a massive group of simple units of process, the neurons. And it is in their connections where
the intelligence of the network is placed. We plan to tackle the backpropagation algorithm both in theoretical and practical approaches so we can build an object recognition system. |
|
| dc.format |
54 p. |
|
| dc.format |
application/pdf |
|
| dc.language |
cat |
|
| dc.rights |
cc-by-nc-nd (c) Andrea Navarro i López, 2016 |
|
| dc.rights |
codi: GPL (c) Andrea Navarro i López, 2016 |
|
| dc.rights |
http://creativecommons.org/licenses/by-nc-nd/3.0/es |
|
| dc.rights |
http://www.gnu.org/licenses/gpl-3.0.ca.html |
|
| dc.rights |
info:eu-repo/semantics/openAccess |
|
| dc.source |
Treballs Finals de Grau (TFG) - Matemàtiques |
|
| dc.subject |
Xarxes neuronals (Informàtica) |
|
| dc.subject |
Treballs de fi de grau |
|
| dc.subject |
Neurones |
|
| dc.subject |
Aprenentatge automàtic |
|
| dc.subject |
Algorismes computacionals |
|
| dc.subject |
Neural networks (Computer science) |
|
| dc.subject |
Bachelor's theses |
|
| dc.subject |
Neurons |
|
| dc.subject |
Machine learning |
|
| dc.subject |
Computer algorithms |
|
| dc.title |
Estudi sobre les xarxes neuronals artificials |
|
| dc.type |
info:eu-repo/semantics/bachelorThesis |
|