We generally think of plugging new input/output devices into a computer and turning it on to get something new. But with this model, the previously stored data is changed by the new parts, too.

This paper develops a frequency-domain iterative machine learning (IML) approach for output tracking. Frequency-domain iterative learning control allows bounded noncausal inversion of system dynamics ...

Banks and insurance companies. Banks and insurance companies rely on machine learning to detect and prevent fraud through subtle signals of strange behavior and unexpected transactions ...

With the advent of 5G and next-generation communication systems, massive multiple-input multiple-output technology is critical for enhancing spectral efficiency and link reliability. However, as the ...

Keywords: Computer vision, Image processing, Machine Learning, Probabilistic Models, Visual Intelligence, Histopathology Research group: Digital Signal Processing and Image Analysis (DSB) This ...

The output is 5V for input signals lower than this level. If the input signal exceeds 5V, the output voltage drops to 0V (b). Sometimes, a zero-output signal is undesirable. A missing power-supply ...

We further investigate the Joint Channel Estimation And Signal Detection architecture so that our signal detectors can take output of our probabilistic channel estimator. And we also investigate the ...