This repository is for DA623: Computing with Signals course project. It contains a tutorial demonstrating the Shannon reconstruction: effects on . da623_assign_200103102.ipynb : Jupyter notebook ...
Datasets can be highly unbalanced: some values/categories may be over-represented, while others may be under-represented. Such imbalance may have a negative impact on many machine learning techniques: ...
Analog measurement resources in today’s mixed-signal ATE use ADCs, and the test methodologies are based on DSP. Two types of measurement resources are distinguished by the relationship of the test ...
This undersampling technique can be applied to applications such as harmonic sampling, IF sampling, and direct IF-to-digital conversion. However, in applications such as AC strain gauges or other ...
In undersampling applications, such as wideband receivers, cellular base stations, and communications receivers, the undersampled signal has a relatively low-frequency bandwidth—with the help of the ...
Abstract: Undersampling is a widely adopted method to deal with imbalance pattern classification problems. Current methods mainly depend on either random resampling on the majority class or resampling ...
Abstract: Random-based UnderSampling (RUS) methods for imbalanced pattern classification problems suffer from high variance problems. Therefore, the Inverse RUS (IRUS) is proposed to relieve this ...
In this study, we demonstrated generation and transmission of 114 Gbaud and 126 Gbaud faster-than-Nyquist (FTN) discrete Fourier transform-spread (DFT-spread) quadrature phase shift keying orthogonal ...
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