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We present a real-time version of the DUET algorithm forthe blind separation of any number of sources using only two mixtures. The method applies when sources are Wdisjoint orthogonal, that is, when t...
We investigate the assumption that sources have disjoint support in the time domain, time-frequency domain, or frequency domain. We call such signals disjoint orthogonal. The class of signals that app...
Few source separation and independent component analysis approaches attempt to deal with noisy data. Weconsider an additive noise mixing model with an arbitrary number of sensors and possibly more sou...
To be applicable in realistic scenarios, blind source separation approaches should deal evenly with non-square cases and the presence of noise. We consider an additive noisemixing model with an arbitr...
Sparse constraints on signal decompositions are justified bytypical sensor data used in a variety of signal processing fields such as acoustics, medical imaging, or wireless, but moreover can lead to ...
In this paper I present a Minimum Description Length Estimator for number of sources in an anechoic mixture of sparse signals.The criterion is roughly equal to the sum of negative normalized maximum l...
We consider linear inverse problems in a nonparametric statistical framework. Both the signal and the operator are unknown and subject to error measurements. We establish minimax rates of convergence ...
We consider a zero sum differential game with lack of observation on one side. The initial state of the system is drawn at random according to some probability μ0 on IRN. Player I is informed of the i...
Chen, Qiu, and Zheng proposed a Rabin-like blind signature scheme, which is based on the square-root problem. Although their scheme is simple and efficient, it can be compromised when choosing some pa...

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