ブラインド音源分離 (Blind Source Separation; BSS) とは,音源の成分と音源からマイクロホンま での伝達特性がともに未知のもとで,マイクロホン入 力信号から音源成分を復元する技術である。音声信号 を対象とした BSSは,ハンズフリーテレビ会議システ ムなど,多くの応用が期待されている。 以下,まず BSS の問題を定式化する。M 個の信 号源から到来する音源信号を J 個のマイクロホン で観測する場合を考え,j 番目のマイクロホンで 観測される信号の時間周波数成分を yj(ω, t),m 番 目の音源信号の時間周波数成分を sm(ω, t) とし, y(ω, t) = (y1(ω, t), . . . , yJ(ω, t)) T ∈ C,s(ω, t) = (s1(ω, t), . . . , sM (ω, t)) T ∈ C とする。ただし, 1 ≤ ω...

In this paper, we will focus on the problem of blind source separation for independent and identically distributed variables (iid). The problem may be stated as follows: we observe a linear (unknown) mixture of k iid variables (the sources), and we want to recover either the sources or the linear mapping. We give online stability conditions of the algorithm using the eigenvalues of the hessian ...

time domain beamforming and blind source separation speech input in the car environment lecture notes in electrical engineering What to say and what to do when mostly your friends love reading? Are you the one that don't have such hobby? So, it's important for you to start having that hobby. You know, reading is not the force. We're sure that reading will lead you to join in better concept of l...

A high-precision method is presented for the extraction of the fetal electrocardiogram from multi-channel potential recordings on the mother's skin. First the problem is appropriately formulated in terms of blind source separation, where the sources can have a multi-dimensional nature. As a summary of preceding work it is shown how the fetal electrocardiogram can be reconstructed by means of se...

Time-domain methods for blind separation of audio signals are preferred due to their lower demand for available data and the avoidance of the permutation problem. However, their computational demands increase rapidly with the length of separating filters due to the simultaneous growth of the dimension of an observation space. We propose, in this paper, a general framework that allows the time-d...

In this paper we present a simple method to deal with Blind Source Separation (BSS) of Finite Impulse Response (FIR) convolutive mixtures. The global method proceeds in two steps. The first step consists in separating each source contribution in the mixture. This step provides several filtered version of each source. The second step consists in retrieving the original sources from the set of fi...

Neutron and muon monitor networks can be used as single multidirectional spectrograph, thereby improving the detection of Ground Level Enhancements (GLEs) and of signatures from approaching interplanetary disturbances (Usoskin et al., 1997; Mavromichalaki et al., 2004). The real-time analysis of such network data, however, is often hampered by a number of practical difficulties such as data gap...

In the context of relating specific brain functions to specific brain structures, second-order blind identification (SOBI) is one of the blind source separation algorithms that have been validated extensively in the data domain of human high-density EEG. Here we provide a review of empirical data that (1) validate the claim that SOBI is capable of separating correlated neuronal sources from eac...

We present a new technique for achieving source separation when given only a single channel recording. The main idea is based on exploiting the inherent time structure of sound sources by learning a priori sets of basis filters in time domain that encode the sources in a statistically efficient manner. We derive a learning algorithm using a maximum likelihood approach given the observed single ...