We propose a technique to separate audio sources from their anechoic mixtures with long delay in an underdetermined setting (i.e., the number of audio sensors is smaller than that...
We develop energy-efficient, adaptive distributed transforms for data gathering in wireless sensor networks. In particular, we consider a class of unidirectional transforms that ...
In this paper we present a novel approach for sampling and reconstructing any K-sided convex and bilevel polygon with the use of exponential splines [1]. It will be shown that wit...
In this paper we consider the problem of sampling far below the Nyquist rate signals that are sparse linear superpositions of shifts of a known, potentially wide-band, pulse. This...
This paper proposes a set of affine invariant features (AIFs) for sequence data. The proposed AIFs can be calculated directly from the sequence data, and their invariance to af...
In this paper, we propose a distributed solution to the problem of configuring classifier trees in distributed stream mining systems. The configuration involves selecting appro...
Hyunggon Park, Deepak S. Turaga, Olivier Verscheur...
The use of psychoacoustical masking models for audio coding applications has been wide spread over the past decades. In such applications, it is typically assumed that the origina...
Time-frequency representations of audio signals often resemble texture images. This paper derives a simple audio classification algorithm based on treating sound spectrograms as ...
In this paper, we propose to use the scaling ambiguity of convolutive blind source separation for shortening the unmixing filters. An often used approach for separating convoluti...
This paper describes a method for designing oversampled DFT filter banks (FB) optimized for subband acoustic echo cancellation (AEC). For this application, the design requirements...