In this paper we propose extension of multichannel blind equalization problem assuming that both mixing and demixing models are described by stable linear state-space systems. The problem is formulated as an optimization task. New learning algorithms are developed which can be considered as extension of existing algorithms. By applying demixing state-space model we will be able to reduce comple...

Recently, Kundur and Hatzinakos showed that a linear restoration filter designed by using the almost obvious a priori knowledge on the original image, such as (i) nonnegativity of the true image and (ii) the smallest rectangle encompassing the original object, can realize a remarkable performance for a blind image deconvolution problem. In this paper, we propose a new set-theoretic blind image ...

Blind Source Separation (BSS) is often carried out under the assumption that sources are statistically mutually independent, at least in the sense of cumulants of given order. However, this assumption is not mandatory, and can be replaced by some assumption on the source distribution, even if all sources are identically distributed. Contrast functions are optimization criteria that satisfy some...

We present a simple but efficient and powerful extension of standard Bussgang-type blind equalization algorithms that is able to extract multiple source signals from their unknown convolutive mixtures. The extraction of source signals one by one using a deflation approach is proposed. A new adaptive deflation algorithm which can cancel the contribution of already extracted source signals, is de...

Biomedical images are often degraded during image acquisition. Two very common degradations that occur in many biomedical imaging modalities are blur and noise. Corrupted images are more difficult to interpret by the physician or researcher and so the goal is to restore the original image. Blurring can be mathematically modeled by convolution, and within this model the blur is characterized by ...

This paper explores blind deconvolution of reverberated speech signals in microphone array applications. Two regularization approaches are proposed based on available a priori knowledge. The regularized least–square approach uses the speech signal characteristics and the lowpass nature of the reverberation channel; and the regularized cross–correlation approach requires more precise knowledge o...