In this paper, we propose a real-time BSS (Blind Source Separation) system with two microphones that extracts only desired sound sources. Under the assumption that the desired sound sources are close to the microphones, the proposed BSS system suppresses distant sound sources as undesired sound sources. We previously developed a BSS system that can estimate the distance from a microphone to a sound source and suppress distant sound sources, but it was not a real-time processing system. The proposed BSS system is a real-time version of our previous BSS system. To develop the proposed BSS system, we simplify some BSS procedures of the previous system. Simulation results showed that the proposed system can effectively suppress the distant source signals in real-time and has almost the same capability as the previous system.

Moment invariants of a discrete image are not strictly invariant to image displacements due to quantization errors. This letter introduces a weighting function such that the pixel value is smoothly reduced to zero at the boundary of the image. Image moments of the weighted image are robust against quantization errors, and the moment invariants of the weighted image are more invariant than those of the unweighted image.

This paper proposes an adaptive comb filter with flexible notch gain. It can appropriately remove a periodic noise from an observed signal. The proposed adaptive comb filter uses a simple LMS algorithm to update the notch gain coefficient for removing the noise and preserving a desired signal, simultaneously. Simulation results show the effectiveness of the proposed comb filter.