This paper describes the circularity problem of frequencydomain blind source separation (BSS), and presents a new method for solving it. Frequency-domain BSS performs independent component analysis (ICA) in each frequency bin. It is more efficient than time-domain BSS where ICA is applied to convolutive mixtures. However, frequency-domain BSS has two problems. The first is the permutation probl...

Blind source separation (BSS) and sound activity detection (SAD) from a sound source mixture with minimum prior information are two major requirements for computational auditory scene analysis that recognizes auditory events in many environments. In daily environments, BSS suffers from many problems such as reverberation, a permutation problem in frequency-domain processing, and uncertainty abo...

Using the sparsity property in the frequency domain of harmonic signals, this paper gives a harmonic extraction algorithm based on multi-resolution blind source separation (BSS) method. After the general and detailed definition of the multi-resolution BSS model is given, the wavelet packet decomposition based multiresolution BSS algorithm for harmonic signal extraction is constructed in detail....

Blind source separation (BSS) is a problem found in many applications related to acoustics or communications. This paper addresses the blind source separation problem for the case where the source signals are non-stationary and the sensors are noisy. To this end, we propose several useful elementary cost functions which can be combined to an overall cost function. The elementary cost functions ...

In this paper, we propose a robust blind multiuser detector for code-division multiple access (CDMA) systems against signature waveform mismatch (SWM) derived from the influences of time asynchronization or channel distortion. This blind detection method with SWM problem is formulated as blind source separation (BSS) model subject to the second-order cone (SOC) constraint. The resulting blind s...

In this paper, a Blind Source Separation (BSS) algorithm for multichannel audio contents is proposed. Unlike common BSS algorithms targeting stereo audio contents or microphone array signals, our technique is targeted at multichannel audio such as 5.1 and 7.1ch audio. Since most multichannel audio object sources are panned using the Inter-channel Loudness Difference (ILD), we employ the ILVS (I...

We address the problem of Blind Source Separation (BSS) of superimposed signals in situations where one signal has constant or slowly varying intensities at some consecutive locations and at the corresponding locations the other signal has highly varying intensities. Independent Component Analysis (ICA) is a major technique for Blind Source Separation and the existing ICA algorithms fail to est...

Separating vibration signals generated by defective rolling bearings is of major importance for rotating machinery health monitoring, since rolling bearings of the same type are quite frequently encountered in the industrial environment, especially in large machines, critical in the production process. For this reason, Blind Source Separation (BSS) is considered for application on vibration sig...

In the signal processing area, blind source separation (BSS) is a method aiming to recover independent sources from their linear instantaneous mixtures without resorting to any prior knowledge, such as mixing matrices and sources. There have been increased attentions given to blind source separation in many areas, including wireless communication, biomedical imaging processing, multi-microphone...

The problem of multiuser detection in wireless communications systems adopts, in flat-fading channels, a blind source separation (BSS) formulation of instantaneous linear mixtures. This contribution addresses the closed-form solutions to BSS in the complex-mixture scenario. The algebraic devices which span a unifying framework for the complex BSS closed-form estimators are developed. With the a...