praca-magisterska/docs/document.toc

\contentsline {chapter}{Streszczenie}{7}% 
\contentsline {chapter}{Abstract}{9}% 
\contentsline {chapter}{Wst\IeC {\k e}p}{11}% 
\contentsline {chapter}{Rozdzia\PlPrIeC {\l }\ 1\relax .\leavevmode@ifvmode \kern .5em Wprowadzenie do sieci neuronowych}{13}% 
\contentsline {section}{\numberline {1.1\relax .\leavevmode@ifvmode \kern .5em }Regresja liniowa}{13}% 
\contentsline {section}{\numberline {1.2\relax .\leavevmode@ifvmode \kern .5em }Uczenie modelu}{14}% 
\contentsline {subsection}{\numberline {1.2.1\relax .\leavevmode@ifvmode \kern .5em }Funkcja kosztu}{15}% 
\contentsline {subsection}{\numberline {1.2.2\relax .\leavevmode@ifvmode \kern .5em }Znajdowanie minimum funkcji}{15}% 
\contentsline {subsection}{\numberline {1.2.3\relax .\leavevmode@ifvmode \kern .5em }Metody gradientowe}{15}% 
\contentsline {section}{\numberline {1.3\relax .\leavevmode@ifvmode \kern .5em }Regresja liniowa jako model sieci neuronowej}{17}% 
\contentsline {section}{\numberline {1.4\relax .\leavevmode@ifvmode \kern .5em }Funkcje aktywacji}{19}% 
\contentsline {section}{\numberline {1.5\relax .\leavevmode@ifvmode \kern .5em }Wielowarstwowe sieci neuronowe}{19}% 
\contentsline {subsection}{\numberline {1.5.1\relax .\leavevmode@ifvmode \kern .5em }Jednokierunkowe sieci neuronowe}{20}% 
\contentsline {subsection}{\numberline {1.5.2\relax .\leavevmode@ifvmode \kern .5em }Autoencoder}{21}% 
\contentsline {subsection}{\numberline {1.5.3\relax .\leavevmode@ifvmode \kern .5em }Rekurencyjne sieci neuronowe}{22}% 
\contentsline {subsection}{\numberline {1.5.4\relax .\leavevmode@ifvmode \kern .5em }LSTM}{23}% 
\contentsline {subsection}{\numberline {1.5.5\relax .\leavevmode@ifvmode \kern .5em }Sequence-to-sequence}{26}% 
\contentsline {chapter}{Rozdzia\PlPrIeC {\l }\ 2\relax .\leavevmode@ifvmode \kern .5em Wprowadzenie do teorii muzyki}{27}% 
\contentsline {section}{\numberline {2.1\relax .\leavevmode@ifvmode \kern .5em }Podstawowe koncepcje muzyczne}{27}% 
\contentsline {subsection}{\numberline {2.1.1\relax .\leavevmode@ifvmode \kern .5em }D\IeC {\'z}wi\IeC {\k e}k muzyczny}{27}% 
\contentsline {subsection}{\numberline {2.1.2\relax .\leavevmode@ifvmode \kern .5em }Sygna\IeC {\l } d\IeC {\'z}wi\IeC {\k e}kowy}{27}% 
\contentsline {subsection}{\numberline {2.1.3\relax .\leavevmode@ifvmode \kern .5em }Zapis nutowy}{27}% 
\contentsline {section}{\numberline {2.2\relax .\leavevmode@ifvmode \kern .5em }Cyfrowa reprezentacja muzyki symbolicznej}{31}% 
\contentsline {subsection}{\numberline {2.2.1\relax .\leavevmode@ifvmode \kern .5em }Standard MIDI}{31}% 
\contentsline {chapter}{Rozdzia\PlPrIeC {\l }\ 3\relax .\leavevmode@ifvmode \kern .5em Projekt}{35}% 
\contentsline {section}{\numberline {3.1\relax .\leavevmode@ifvmode \kern .5em }Koncepcja}{35}% 
\contentsline {section}{\numberline {3.2\relax .\leavevmode@ifvmode \kern .5em }Wst\IeC {\k e}pne przygotowanie danych do treningu}{36}% 
\contentsline {subsection}{\numberline {3.2.1\relax .\leavevmode@ifvmode \kern .5em }Muzyczne ,,s\IeC {\l }owo''}{36}% 
\contentsline {subsection}{\numberline {3.2.2\relax .\leavevmode@ifvmode \kern .5em }Konwersja MIDI na sekwencje s\IeC {\l }\IeC {\'o}w muzycznych}{36}% 
\contentsline {subsection}{\numberline {3.2.3\relax .\leavevmode@ifvmode \kern .5em }Inne aspekty przygotowania danych}{39}% 
\contentsline {subsection}{\numberline {3.2.4\relax .\leavevmode@ifvmode \kern .5em }Podzia\IeC {\l } danych na dane wej\IeC {\'s}ciowe i wyj\IeC {\'s}ciowe}{40}% 
\contentsline {subsection}{\numberline {3.2.5\relax .\leavevmode@ifvmode \kern .5em }Inne aspekty przygotowania zbioru ucz\IeC {\k a}cego}{42}% 
\contentsline {section}{\numberline {3.3\relax .\leavevmode@ifvmode \kern .5em }Definicja modelu}{44}% 
\contentsline {subsection}{\numberline {3.3.1\relax .\leavevmode@ifvmode \kern .5em }Model w trybie uczenia}{44}% 
\contentsline {subsection}{\numberline {3.3.2\relax .\leavevmode@ifvmode \kern .5em }Model w trybie wnioskowania}{46}% 
\contentsline {section}{\numberline {3.4\relax .\leavevmode@ifvmode \kern .5em }Transformacja danych dla modelu}{49}% 
\contentsline {subsection}{\numberline {3.4.1\relax .\leavevmode@ifvmode \kern .5em }Enkodowanie one-hot}{49}% 
\contentsline {subsection}{\numberline {3.4.2\relax .\leavevmode@ifvmode \kern .5em }S\IeC {\l }ownik}{49}% 
\contentsline {subsection}{\numberline {3.4.3\relax .\leavevmode@ifvmode \kern .5em }Elementy specjalne}{50}% 
\contentsline {subsection}{\numberline {3.4.4\relax .\leavevmode@ifvmode \kern .5em }Zakodowanie sekwencji}{50}% 
\contentsline {section}{\numberline {3.5\relax .\leavevmode@ifvmode \kern .5em }Ekperyment}{51}% 
\contentsline {subsection}{\numberline {3.5.1\relax .\leavevmode@ifvmode \kern .5em }Oprogramowanie}{52}% 
\contentsline {subsection}{\numberline {3.5.2\relax .\leavevmode@ifvmode \kern .5em }Zbi\IeC {\'o}r danych}{52}% 
\contentsline {subsection}{\numberline {3.5.3\relax .\leavevmode@ifvmode \kern .5em }Wydobycie danych}{52}% 
\contentsline {section}{\numberline {3.6\relax .\leavevmode@ifvmode \kern .5em }Trenowanie modelu}{53}% 
\contentsline {section}{\numberline {3.7\relax .\leavevmode@ifvmode \kern .5em }Generowanie muzyki przy pomocy wytrenowanych modeli}{54}% 
\contentsline {section}{\numberline {3.8\relax .\leavevmode@ifvmode \kern .5em }Wyniki}{56}% 
\contentsline {section}{\numberline {3.9\relax .\leavevmode@ifvmode \kern .5em }Wnioski}{56}% 
\contentsline {chapter}{Rozdzia\PlPrIeC {\l }\ 4\relax .\leavevmode@ifvmode \kern .5em Podsumowanie}{57}% 
\contentsline {chapter}{Bibliografia}{59}%