Results 251 to 260 of about 93,524 (286)

Oversampled receive array calibration

2015 23rd European Signal Processing Conference (EUSIPCO), 2015
The problem of receive antenna array calibration in cases where the array is strongly spatially "over-sampled" is addressed in this paper. We suggest a new technique wherein spatially distributed strong clutter returns can be used for calibration with the goal of minimizing the power at the output of a number of antenna finger-beams steered into the ...
Yuri I. Abramovich, Geoffrey San Antonio
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Oversampled transforms for channels with erasures

Proceedings of the IEEE Information Theory Workshop, 2003
Oversampled transforms are used to provide robustness against erasures. Oversampled DFT codes have already been studied for erasure channels Me IP networks. We propose oversampled DCT transforms called DCT codes for erasure channels. We show that DCT codes offer more flexibility in design as compared to DFT codes and for some cases, lesser average mean
openaire   +1 more source

Increased information rate by oversampling

IEEE Transactions on Information Theory, 1993
A noiseless ideal low-pass filter, followed by a limiter, is normally used as a binary data channel by sampling the output once per Nyquist interval. Detectors that sample more often encounter intersymbol interference, but can be used in ways that increase the information rate.
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On optimum oversampling in the Gabor scheme

1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002
The windowed Fourier transform of a time signal is considered, as well as a way to reconstruct the signal from a sufficiently densely sampled version of its windowed Fourier transform using a Gabor representation; following Gabor, sampling occurs on a two-dimensional time-frequency lattice with equidistant time intervals and equidistant frequency ...
openaire   +1 more source

RAMOBoost: Ranked Minority Oversampling in Boosting

IEEE Transactions on Neural Networks, 2010
In recent years, learning from imbalanced data has attracted growing attention from both academia and industry due to the explosive growth of applications that use and produce imbalanced data. However, because of the complex characteristics of imbalanced data, many real-world solutions struggle to provide robust efficiency in learning-based ...
Chen, Sheng, He, Haibo, Garcia, Edwardo A.   +2 more
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Turbo Quantization of Oversampled Signals

IEEE Transactions on Information Theory, 2016
We present a new iterative quantization procedure for oversampled frames with guaranteed convergence and stability. The procedure uses similar concepts to that of turbo decoding in the context of error control coding. The quantization process is modeled as a quadratic integer-programming problem.
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Analytical treatment of oversampling

Experimental Astronomy, 1990
During searches for periodicity in very high energy (VHE) gamma ray data, the freedom usually exists to place a trial period anywhere within the spacing between independent periods normally associated with a Fourier transform of data of finite duration.
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Investigation on the stability of SMOTE-based oversampling techniques in software defect prediction

Information and Software Technology, 2021
Shuo Feng, Jacky Keung, Yan Xiao
exaly  

Conditional Wasserstein GAN-based oversampling of tabular data for imbalanced learning

Expert Systems With Applications, 2021
Justin Engelmann, Stefan Lessmann
exaly  

An efficient method to determine sample size in oversampling based on classification complexity for imbalanced data

Expert Systems With Applications, 2021
Dohyun Lee, Kyoungok Kim
exaly