We consider the problem of non-negative super-resolution, which concerns reconstructing a signal x=?i=1kai?ti from m samples its convolution with window function ?(s?t), form y(sj)=?i=1kai?(sj?ti)+?j, where ?j indicates an inexactness in sample value. first show that x is unique measure consistent samples, provided are exact. Moreover, we characterise solutions xˆ within bound ?j=1m?j2??2. inte...

Source separation arises in a variety of signal processing applications, ranging from speech processing to medical image analysis. The separation of a superposition of multiple signals is accomplished by taking into account the structure of the mixing process and by making assumptions about the sources. When the information about the mixing process and sources is limited, the problem is called ...

Sparse representation based classification (SRC) has been proved to be a simple, effective and robust solution to face recognition. As it gets popular, doubts on the necessity of enforcing sparsity starts coming up, and primary experimental results showed that simply changing the l1-norm based regularization to the computationally much more efficient l2-norm based non-sparse version would lead ...