TY  - JOUR
AB  - Signals, recorded over time, are often observed as mixtures of multiple source signals. To extract relevant information from such measurements one needs to determine the mixing coefficients. In case of weakly stationary time series with uncorrelated source signals, this separation can be achieved by jointly diagonalizing sample autocovariances at different lags, and several algorithms address this task. Often the mixing estimates contain close-to-zero entries and one wants to decide whether the corresponding source signals have a relevant impact on the observations or not. To address this question of model selection we consider the recently published second-order blind identification procedures SOBIdef and SOBIsym which provide limiting distributions of the mixing estimates. For the first time, such distributions enable informed decisions about the presence of second-order stationary source signals in the data. We consider a family of linear hypothesis tests and information criteria to perform model selection as second step after parameter estimation. In simulations we consider different time series models. We validate the model selection performance and demonstrate a good recovery of the true zero pattern of the mixing matrix.
AU  - Illner, K.
AU  - Miettinen, J.*
AU  - Fuchs, C.
AU  - Taskinen, S.*
AU  - Nordhausen, K.*
AU  - Oja, H.*
AU  - Theis, F.J.
C1  - 43275
C2  - 36284
CY  - Amsterdam
SP  - 95-103
TI  - Model selection using limiting distributions of second-order blind source separation algorithms.
JO  - Signal Process.
VL  - 113
PB  - Elsevier Science Bv
PY  - 2015
SN  - 0165-1684
ER  - 

TY  - JOUR
AB  - We transfer the ICA model to the case where the underlying field is not the set of teals but an arbitrary finite field. We give conditions for separability of the model, pointing out existing parallels to the real case. Three algorithms capable of solving the task are suggested and we demonstrate their viability through simulations and a possible application of the model.
AU  - Gutch, H.W.*
AU  - Gruber, P.*
AU  - Yeredor, A.*
AU  - Theis, F.J.
C1  - 24305
C2  - 31500
SP  - 1796-1808
TI  - ICA over finite fields - separability and algorithms.
JO  - Signal Process.
VL  - 92
IS  - 8
PB  - Elsevier Science
PY  - 2012
SN  - 0165-1684
ER  - 

TY  - JOUR
AB  - We present the outcomes of three recent evaluation campaigns in the field of audio and biomedical source separation. These campaigns have witnessed a boom in the range of applications of source separation systems in the last few years, as shown by the increasing number of datasets from 1 to 9 and the increasing number of submissions from 15 to 34. We first discuss their impact on the definition of a reference evaluation methodology, together with shared datasets and software. We then present the key results obtained over almost all datasets. We conclude by proposing directions for future research and evaluation, based in particular on the ideas raised during the related panel discussion at the Ninth International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2010).
AU  - Vincent, E.*
AU  - Araki, S.*
AU  - Theis, F.J.
AU  - Nolte, G.*
AU  - Bofill, P.*
AU  - Sawada, H.*
AU  - Ozerov, A.*
AU  - Gowreesunker, V.*
AU  - Lutter, D.
AU  - Duong, N.Q.K.*
C1  - 8042
C2  - 29953
SP  - 1928-1936
TI  - The signal separation evaluation campaign (2007-2010): Achievements and remaining challenges.
JO  - Signal Process.
VL  - 92
IS  - 8
PB  - Elsevier Science
PY  - 2011
SN  - 0165-1684
ER  - 

TY  - JOUR
AB  - This paper proposes a new method for image compression. The method is based on the approximation of an image, regarded as a function, by a linear spline over an adapted triangulation, D(Y), which is the Delaunay triangulation of a small set Y of significant pixels. The linear spline minimizes the distance to the image, measured by the mean square error, among all linear splines over D(Y). The significant pixels in Y are selected by an adaptive thinning algorithm, which recursively removes less significant pixels in a greedy way, using a sophisticated criterion for measuring the significance of a pixel. The proposed compression method combines the approximation scheme with a customized scattered data coding scheme. We compare our compression method with JPEG2000 on two geometric images and on three popular test cases of real images.
AU  - Demaret, L.
AU  - Dyn, N.
AU  - Iske, A.*
C1  - 4184
C2  - 28271
CY  - Amsterdam
SP  - 1604-1616
TI  - Image compression by linear splines over adaptive triangulations.
JO  - Signal Process.
VL  - 86
IS  - 7
PB  - Elsevier Science BV
PY  - 2006
SN  - 0165-1684
ER  - 

TY  - JOUR
AB  - A recurrence relation is established which allows to calculate in a simple manner the n-fold convolution power of an arbitrary sum of pulse functions.
AU  - Lasser, R.H.
C1  - 40879
C2  - 40300
SP  - 93-96
TI  - On the evaluation of the n-fold convolution power of sums of rectangular pulse functions.
JO  - Signal Process.
VL  - 12
IS  - 1
PY  - 1987
SN  - 0165-1684
ER  -