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This paper addresses the blind signal separation problem in the presence of sensor noise for the case where the source signals are non-stationary and / or non-white. This problem can be formulated as a joint-diagonalization problem where the objective is to jointly diagonalize a set of correlation matrices {Rp}, using a single matrix W. We derive a Newton-type algorithm for two joint-diagonalization cost functions, which are related to the aforementioned blind signal separation problem. To this end, we derive the gradient and also the Hessian of the joint diagonalization cost function in closed form. The most general case is considered, in which the source signals and the unknown mixing matrix are assumed to be complex.

In this paper we present a new method for separating non-stationary sources from their convolutive mixtures based on approximate joint diagonalization of the observed signals' cross-spectral density matrices. Several blind source separation (BSS) algorithms have been proposed which use approximate joint diagonalization of a set of scalar matrices to estimate the instantaneous mixing matrix. We extend the concept of approximate joint diagonalization to estimate MIMO FIR channels. Based on this estimate we then design a separating network which will recover the original sources up to only a permutation and scaling ambiguity for minimum phase channels. We eliminate the commonly experienced problem of arbitrary scaling and permutation at each frequency bin, by optimizing the cost function directly with respect to the time-domain channel variables. We demonstrate the performance of the algorithm by computer simulations using real speech data. Speech samples are available at: http://sparky.mcmaster.ca/SSP/telephonylcamran.htm. * lar to [6] and [I 11 in this respect, in that all of them use secondorder time-varying cross-spectral information, assuming that the sources are non-stationary. The primary differences between the proposed method and the previous methods are 1) we estimate the channel directly, and 2) we eliminate the common difficult problem of arbitrary permutation and scaling at each frequency bin by directly optimizing a new cost function (formulated in frequency domain) with respect to the channel coefficients. Also the previous methods separate the sources only up to afilfered version of original sources. With the proposed method, under the assumption that the order of channel is known, it is possible to recover the sources up to a scaled version of the original sources. Notice that in the case of separation, the separation system output is a permuted and jiltered version of the sources, while in the case of recovery, the outputs are only a scaled and permuted version of the sources. Numerical simulation using real speech data have been presented to demonstrate the performance of the algorithm.

Patients with arrhythmogenic right ventricular cardiomyopathy (ARVC) typically present with ventricular tachyarrhythmias preferentially triggered by an elevated sympathetic tone. Previous studies demonstrated an impairment of the presynaptic catecholamine reuptake as assessed by 123 I-labeled norepinephrine analog on metaiodobenzylguanidine ( 123 I-MIBG) SPECT. Mutations in the gene encoding for plakophilin-2 (PKP-2) are the most common cause of autosomal dominant ARVC (ARVC-9). In this study, we investigated the potential role of adrenergic dysfunction on the arrhythmia profile in patients with ARVC and correlated these findings with the causative genotype. Methods: 123 I-MIBG SPECT was performed for 42 patients with definite ARVC (10 women, 32 men; mean age 6 SD, 43 6 14 y). Images were acquired at 4 h after injection and analyzed for regional 123 I-MIBG uptake in a standardized 33-segment polar map. Results were compared with those obtained from 10 control subjects (5 women, 5 men; mean age 6 SD, 43 6 12 y). Results: An abnormal tracer uptake was detected in 25 patients with ARVC (59%). The extents of right ventricular dilation and regional wall motion abnormalities as well as electrocardiographic markers of de-or repolarization were not significantly different between patients with normal and abnormal 123 I-MIBG SPECT findings. However, during long-term follow-up of 11.9 6 4.1 y, patients with abnormal 123 I-MIBG SPECT findings experienced life-threatening ventricular tachyarrhythmias significantly more often (22/25 patients [88%]) and independent of the extent of right ventricular dysfunction than those with a normal sympathetic innervation (6/17 patients [35%]; P , 0.0005). Mutations in PKP-2 were identified in 17 patients (40%) but were not correlated with the degree of adrenergic dysfunction. Conclusion: In patients with ARVC, an impairment of adrenergic innervation independent of the underlying genotype is associated with a higher incidence for future recurrences of ventricular tachyarrhythmias. This finding may suggest a potential role of 123 I-MIBG SPECT for individualized risk stratification in ARVC patients and asymptomatic PKP-2 mutation carriers alike.

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