Sökning: "Recurrent Neuralt Network"

Visar resultat 11 - 15 av 27 uppsatser innehållade orden Recurrent Neuralt Network.

1. 11. Unsupervised learning of data representations in brain-like neural networks

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Arian Javdan; [2021]
   Nyckelord :;

   Sammanfattning : Recently, there has been a growing interest in brain-plausible neural networks that closely resemble the brain’s structure. However, conventional networks do not make good models for the brain since these connections are modelled differently, hence the interest in brain-plausible networks. LÄS MER

3. 12. Applicering av Long Short-Term Memory för prediktion av markdeformation på svensk järnväg : Utveckling av ett artificiellt neuralt nätverk för prediktion av kommande marksättningar på järnvägssträckan mellan Mölndal och Torrekulla

   Kandidat-uppsats, Högskolan Dalarna/Informatik

   Författare :William Wirsén; Martin Leijon; [2020]
   Nyckelord :Artificiell intelligens; artificial neural network; Long Short-Term Memory; InSAR; land subsidence; Recurrent Neural Network; Artificiell intelligens; artificiellt neurala nätverk; Long Short-Term Memory; InSAR; markdeformering; Recurrent Neural Network;

   Sammanfattning : The purpose of this study is to evaluate whether it is possible to predict future land subsidence on the railway line between Mölndal and Torrekulla. The prediction was made using Long Short-Term Memory; an artificial neural network with RNN architecture. LÄS MER

4. 13. Portfolio Performance Optimization Using Multivariate Time Series Volatilities Processed With Deep Layering LSTM Neurons and Markowitz

   Master-uppsats, KTH/Matematisk statistik

   Författare :Aron Andersson; Shabnam Mirkhani; [2020]
   Nyckelord :Recurrent Neural network RNN ; long short-term memory LSTM ; portfolio optimization; markowitz; exponential moving average; sharpe ratio; heteroskedasticity; Markowitz;

   Sammanfattning : The stock market is a non-linear field, but many of the best-known portfolio optimization algorithms are based on linear models. In recent years, the rapid development of machine learning has produced flexible models capable of complex pattern recognition. LÄS MER

5. 14. Reproducing the state of the art in onset detection using neural networks

   Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Björn Lindqvist; [2019]
   Nyckelord :;

   Sammanfattning : Great strides have been made in the state of the art performance of musicial onset detection in recent years with better and better detectors being invented at a fast pace. The current top spot is held by Schlüter and Böck, who in 2014 presented a detector based on a convolutional neural network (CNN) that attained an F-score of 90. LÄS MER

7. 15. MahlerNet : Unbounded Orchestral Music with Neural Networks

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Elias Lousseief; [2019]
   Nyckelord :music; composition; algorithmic composition; neural networks; recurrent neural networks; RNN; variational autoencoder; VAE; LSTM; BALSTM; MusicVAE; PerformanceRNN; BachProp; musik; komposition; algoritmisk komposition; neurala nätverk; recurrent neural networks; RNN; variational autoencoder; VAE; LSTM; BALSTM; MusicVAE; PerformanceRNN; BachProp;

   Sammanfattning : Modelling music with mathematical and statistical methods in general, and with neural networks in particular, has a long history and has been well explored in the last decades. Exactly when the first attempt at strictly systematic music took place is hard to say; some would say in the days of Mozart, others would say even earlier, but it is safe to say that the field of algorithmic composition has a long history. LÄS MER