|
Kategorie: Diplomové, bakalářské práce |
Tento dokument chci!
Práce popisuje základy principu funkčnosti neuronů a vytvoření umělých neuronových sítí. Je zde důkladně popsána struktura a funkce neuronů a ukázán nejpoužívanější algoritmus pro učení neuronů. Základy fuzzy logiky, včetně jejich výhod a nevýhod, jsou rovněž prezentovány. Detailněji je popsán algoritmus zpětného šíření chyb a adaptivní neuro-fuzzy inferenční systém. Tyto techniky poskytují efektivní způsoby učení neuronových sítí.
neural network for voice recognition will programmed.
Within this work, own neural network will built Matlab, using the
presented techniques.
Two different processes take place such systems. These two techniques are often used together for solving engineering
problems, where classic methods are not able provide straightforward correct
solution. INTRODUCTION
A fuzzy system alternative traditional concepts set membership and
logic. Generally, the neuro-fuzzy term means type system characterized for a
similar structure fuzzy controller where the fuzzy sets and rules are adjusted
using neural networks’ tuning techniques iterative way with data vectors (input
and output system data) [1]. The “neuro-
fuzzy” approach was born combination artificial neural networks and fuzzy
logic. Although its basics originate from the ancient Greek philosophy, relatively
new field, and such, leaves much room for development and applications the
leading edge artificial intelligence.1
1.
. The first called the
learning phase, where neural networks adjust their internal parameters. Within this work, try present the foundations
of neural networks along with some the more remarkable difficulties its use with
examples from the field artificial intelligence.
Modern techniques artificial intelligence can found almost all fields of
the human science, however, the biggest usage engineering field. The second,
implementation phase behaves like fuzzy logic system.
The goal the project apply these specific techniques particular examples,
and analyze and present the differences between them. The combination these
two techniques likely produce better results than the two techniques applied
separately
