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A new approach for convolutive blind source separation (BSS) by explicitly exploiting the second-order nonstationarity of signals and operating in the frequency domain is proposed. The algorithm accommodates a penalty function within the cross-power spectrum-based cost function and thereby converts the separation problem into a joint diagonalization problem(More)
Our former report indicates that calcyclin-binding protein or Siah-1-interacting protein (CacyBP/SIP) is over-expressed in the SGC7901/ADR cell line. However, the potential role of CacyBP/SIP in the development of multidrug resistance (MDR) of pancreatic cancer is still uncertain. In this paper, we investigated the role of CacyBP/SIP in MDR of pancreatic(More)
We consider the data-driven dictionary learning problem. The goal is to seek an over-complete dictionary from which every training signal can be best approximated by a linear combination of only a few codewords. This task is often achieved by iteratively executing two operations: sparse coding and dictionary update. The focus of this paper is on the(More)
Preface Outline and Subject of this Book Machine audition is the field of the study of algorithms and systems for the automatic analysis and understanding of sound by machine. It plays an important role in many applications, such as automatic audio indexing for internet searching, robust speech recognition in uncontrolled natural environment, untethered(More)
A novel variable step-size sign natural gradient algorithm (VS-S-NGA) for online blind separation of independent sources is presented. A sign operator for the adaptation of the separation model is obtained from the derivation of a generalized dynamic separation model. A variable step size is also derived to better match the dynamics of the input signals and(More)
A novel approach using non-negative matrix factorization (NMF) for onset detection of musical notes from audio signals is presented. Unlike most commonly used conventional approaches, the proposed method exploits a new detection function constructed from the linear temporal bases that are obtained from a non-negative matrix decomposition of musical spectra.(More)
Recommended by Sergios Theodoridis A novel approach for onset detection of musical notes from audio signals is presented. In contrast to most commonly used conventional approaches, the proposed method features new detection functions constructed from the linear temporal bases that are obtained from the decomposition of musical spectra using nonnegative(More)
The problem of underdetermined blind audio source separation is usually addressed under the framework of sparse signal representation. In this paper, we develop a novel algorithm for this problem based on compressed sensing which is an emerging technique for efficient data reconstruction. The proposed algorithm consists of two stages. The unknown mixing(More)