ETD system

Electronic theses and dissertations repository

 

Tesi etd-06062011-095647


Thesis type
Tesi di laurea specialistica
Author
FESTA, DYLAN
email address
DarkSnail@gmail.com
URN
etd-06062011-095647
Title
Chaos Characterization of Pulse-Coupled Neural Networks in Balanced State
Struttura
SCIENZE MATEMATICHE, FISICHE E NATURALI
Corso di studi
SCIENZE FISICHE
Commissione
relatore Prof. Fronzoni, Leone
Parole chiave
  • Lyapunov vectors
  • Lyapunov exponents
  • ergodic theory
  • balanced state
  • Neural networks
Data inizio appello
22/06/2011;
Consultabilità
completa
Riassunto analitico
In the present work the formalism of Ergodic theory, used for the statistical study of complex,
nonlinear dynamical systems of N ≫ 1 dimensions in general, is applied to the time evolution
of large-scale pulse-coupled neural networks in the so-called balanced state. The aim is to
measure the ergodic properties of such systems, consider how they are related to the network
parameters, and finally characterize dynamically the participation of individual network nodes
(the “neurons”) in the collective dynamics.
File