Fast multispectral deep fusion networks V. Osin; A. Cichocki; E. Burnaev
Bulletin of the Polish Academy of Sciences. Technical sciences,
12/2018, Letnik:
66, Številka:
No 6 (Special Section on Deep Learning: Theory and Practice)
Journal Article
This paper discusses underdetermined (i.e., with more sources than sensors) blind source separation (BSS) using a two-stage sparse representation approach. The first challenging task of this approach ...is to estimate precisely the unknown mixing matrix. In this paper, an algorithm for estimating the mixing matrix that can be viewed as an extension of the DUET and the TIFROM methods is first developed. Standard clustering algorithms (e.g., K-means method) also can be used for estimating the mixing matrix if the sources are sufficiently sparse. Compared with the DUET, the TIFROM methods, and standard clustering algorithms, with the authors' proposed method, a broader class of problems can be solved, because the required key condition on sparsity of the sources can be considerably relaxed. The second task of the two-stage approach is to estimate the source matrix using a standard linear programming algorithm. Another main contribution of the work described in this paper is the development of a recoverability analysis. After extending the results in , a necessary and sufficient condition for recoverability of a source vector is obtained. Based on this condition and various types of source sparsity, several probability inequalities and probability estimates for the recoverability issue are established. Finally, simulation results that illustrate the effectiveness of the theoretical results are presented.
Using the convolutive nonnegative matrix factorization (NMF) model due to Smaragdis, we develop a novel algorithm for matrix decomposition based on the squared Euclidean distance criterion. The ...algorithm features new formally derived learning rules and an efficient update for the reconstructed nonnegative matrix. Performance comparisons in terms of computational load and audio onset detection accuracy indicate the advantage of the Euclidean distance criterion over the Kullback-Leibler divergence criterion.
Individuals with bleeding tendencies are more likely to have blood type O than blood types A, B, or AB. Platelet storage pool deficiencies are a lesser-known group of bleeding disorders which often ...go undiagnosed and may account for a significant number of patients with unexplained bleeding defects. We hypothesized that patients with platelet δ-storage pool deficiency might also have a predominance of type O blood. A retrospective review of medical records of 2,020 patients with unexplained bleeding and evaluated for δ-storage pool deficiency was performed. Correlations between dense granule numbers, blood type, and von Willebrand factor were analyzed for statistical differences. 51.5% of blood samples were blood type O compared to an incidence of 44.0% in the U.S. population. There was a significant association of vWF and blood type O but not with the delta storage pool. There is a preponderance of blood type O in the study population compared to the U.S. population. There is no statistically significant link between blood type O and lower dense granule numbers in this study.
One of the current issues in brain-computer interface (BCI) is how to deal with noisy electroencephalography (EEG) measurements organized as multidimensional datasets (tensors). On the other hand, ...recently, significant advances have been made in multidimensional signal completion algorithms that exploit tensor decomposition models to capture the intricate relationship among entries in a multidimensional signal. We propose to use tensor completion applied to EEG data for improving the classification performance in a motor imagery BCI system with corrupted measurements. Noisy measurements (electrode misconnections, subject movements, etc.) are considered as unknowns (missing samples) that are inferred from a tensor decomposition model (tensor completion). We evaluate the performance of four recently proposed tensor completion algorithms, CP-WOPT (Acar et al. Chemom Intell Lab Syst. 106:41-56, 2011), 3DPB-TC (Caiafa et al. 2013), BCPF (Zhao et al. IEEE Trans Pattern Anal Mach Intell. 37(9):1751-1763, 2015), and HaLRT (Liu et al. IEEE Trans Pattern Anal Mach Intell. 35(1):208-220, 2013), plus a simple interpolation strategy, first with random missing entries and then with missing samples constrained to have a specific structure (random missing channels), which is a more realistic assumption in BCI applications. We measured the ability of these algorithms to reconstruct the tensor from observed data. Then, we tested the classification accuracy of imagined movement in a BCI experiment with missing samples. We show that for random missing entries, all tensor completion algorithms can recover missing samples increasing the classification performance compared to a simple interpolation approach. For the random missing channels case, we show that tensor completion algorithms help to reconstruct missing channels, significantly improving the accuracy in the classification of motor imagery (MI), however, not at the same level as clean data. Summarizing, compared to the interpolation case, all tensor completion algorithms succeed to increase the classification performance by 7–9% (LDA–SVD) for random missing entries and 15–8% (LDA–SVD) for random missing channels. Tensor completion algorithms are useful in real BCI applications. The proposed strategy could allow using motor imagery BCI systems even when EEG data is highly affected by missing channels and/or samples, avoiding the need of new acquisitions in the calibration stage.
Deep Learning: Theory and Practice A. Cichocki; T. Poggio; S. Osowski ...
Bulletin of the Polish Academy of Sciences. Technical sciences,
12/2018, Letnik:
66, Številka:
No 6 (Special Section on Deep Learning: Theory and Practice)
Journal Article
Biogenesis of mitochondrial outer membrane proteins involves their integration into the lipid bilayer. Among these proteins are those that form a single-span topology, but our understanding of their ...biogenesis is scarce. In this study, we found that the MIM complex is required for the membrane insertion of some single-span proteins. However, other such proteins integrate into the membrane in a MIM-independent manner. Moreover, the biogenesis of the studied proteins was dependent to a variable degree on the TOM receptors Tom20 and Tom70. We found that Atg32 C-terminal domain mediates dependency on Tom20, whereas the cytosolic domains of Atg32 and Gem1 facilitate MIM involvement. Collectively, our findings (1) enlarge the repertoire of MIM substrates to include also tail-anchored proteins, (2) provide new mechanistic insights to the functions of the MIM complex and TOM import receptors, and (3) demonstrate that the biogenesis of MOM single-span proteins shows variable dependence on import factors.
Display omitted
•The single-span proteins Atg32 and Msp1 are new substrates of the MIM complex•Different domains of Atg32 mediate dependency on either Tom20 or MIM components•The MIM complex facilitates the membrane insertion of the tail-anchored protein Gem1•The membrane integration of Mcr1 and Fis1 is mainly MIM independent
Biological Sciences; Molecular Biology; Cell Biology; Functional Aspects of Cell Biology
•Design and conduct of a complex measurement campaign in sea conditions.•Measured data conditioning and transferring into multi-dipole model space.•Multi-dipole model synthesis: model structure and ...parameters identification.•Lasso and Ridge regularisation for model overfitting protection.•The leave-one-out concept application for the purpose of model verification.
The paper presents the partial work done within the framework of the EDA Siramis II project focused on magnetic signature reproduction of ships. Reproduction is understood here as the ability to determine the magnetic anomaly of the local Earth magnetic field in any direction and at any measurement depth due to the presence of the analysed object. The B-91 type hydrographic ship Zodiak was selected as the real case study. The work was divided into two main stages: the development of a measurement campaign taking into account physical measurements, and the development of a mathematical model on the basis of the measured values. The measurement campaign included: preparation of the measuring range, selection of equipment for the measurement of magnetic quantities and geographical location, and data recording while the ship passes the measuring point according to the designated course. As a result of the measurement campaign, magnetic flux density components were collected in different positions in relation to the measuring instruments and the ship's heading. A multi-dipole model was used to build the mathematical model in accordance with the idea of inverse modelling. The effectiveness of this model was previously checked on synthetic data of virtual ships generated using the finite element method. Experiments performed with simulation models were helpful in determining the structure of the model, the nature of the data, and the number of samples needed to properly determine the multi-dipole model parameters. The parameters were determined using the nonlinear least squares method according to the idea of data fitting. The classical Ridge and Lasso regularization methods were applied to prevent the developed multi-dipole model from overfitting. Other regularization methods based on GPS accuracy marks and modification of fitness functions were also considered. The verification was done using real data: the data generated by the model was compared with patterns recorded during the Zodiak measurement campaign. High degree of conformity of the shape of characteristics was obtained. Moreover, the correctness of model execution was confirmed by low values of quantitative indices such as RMSE and MAE representing modelling errors. The methodology presented in the paper is quite universal and can be used to determine the signatures of other ferromagnetic objects.
PDF
