2 papers
cs.LG2025
Efficient Time-Series Approximation with Linear Recurrent Neural Networks: Architecture Learning and Predictive Power
Frieder Stolzenburg, Sandra Litz, Olivia Michael +1
Recurrent neural networks are a powerful means to cope with time series. We show how autoregressive linear, i.e., linearly activated recurrent neural networks (LRNNs) can approxima…
cs.SD2024
Periodicity Pitch Detection in Complex Harmonies on EEG Timeline Data
Maria Heinze, Lars Hausfeld, Rainer Goebel +1
An acoustic stimulus, e.g., a musical harmony, is transformed in a highly non-linear way during the hearing process in ear and brain. We study this by comparing the frequency spect…