[1] |
M. Soleymani, I. Santamaria, B. Maham and P.J. Schreier Rate Region of the K-user MIMO Interference Channel with Imperfect TransmittersIn 2020 28th European Signal Processing Conference (EUSIPCO), pp. 1638-1642, 2021 |
[2] |
Y.H. Xiao, D. Ramírez and P.J. Schreier A General Test for the Linear Structure of Covariance Matrices of Gaussian PopulationsIn 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5365-5369, 2020 |
[3] |
C. Lameiro, I. Santamaria and P.J. Schreier Improper Gaussian Signaling for the Two-user Broadcast Channel Treating Interference as NoiseIn ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4829-4833, 2019 |
[4] |
T. Hasija, M. Gölz, M. Muma, P.J. Schreier and A.M. Zoubir Source Enumeration and Robust Voice Activity Detection in Wireless Acoustic Sensor NetworksIn Proc. Asilomar Conf. on Signals, Systems, Computers, 2019 |
[5] |
S. Horstmann, D. Ramírez and P.J. Schreier Two-channel passive detection exploiting cyclostationarityIn Proc. 27th European Signal Proc. Conf. (EUSIPCO), 2019 |
[6] |
C. Lameiro, T. Hasija, T. Marrinan and P.J. Schreier Estimating the Number of Correlated Components Based on Random ProjectionsIn ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5152-5156, 2019 |
[7] |
C. Lameiro, I. Santamaría and P.J. Schreier Benefits of Improper Signaling for Overlay Cognitive RadioIn Proc. Globecom, 2019 |
[8] |
S. Horstmann, D. Ramírez, P.J. Schreier and A. Pries Two-channel passive detection of cyclostationary signals in noise with spatio-temporal structureIn Proc. Asilomar Conf. Signals Syst. Computers, 2019 |
[9] |
M. Soleymani, C. Lameiro, I. Santamaria and P.J. Schreier Energy-Efficient Improper Signaling for K-User Interference ChannelsIn Proc. IEEE European Signal Processing Conference (EUSIPCO), pp. 1409-1413, 2019 |
[10] |
M. Soleymani, C. Lameiro, P.J. Schreier and I. Santamaria Energy-efficient Design for Underlay Cognitive Radio Using Improper SignalingIn IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4769-4773, 2019 |
[11] |
A. Eguizabal, P. J. Schreier and D. RamĂrez MODEL-ORDER SELECTION IN STATISTICAL SHAPE MODELSIn 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP), pp. 1-6, 2018 |
[12] |
T. Marrinan, T. Hasija, C. Lameiro and P. J. Schreier Complete Model Selection in Multiset Canonical Correlation AnalysisIn Proc. European Signal Process. Conf. (EUSIPCO), pp. 1082-1086, 2018 |
[13] |
J. Tong, Q. Guo, J. Xi, Y. Yu and P. J. Schreier Regularized lattice reduction-aided ordered successive interference cancellation for MIMO detectionIn Proc. IEEE Workshop on Statistical Signal Processing, 2018 |
[14] |
Mohammad Soleymani, C. Lameiro, P.J. Schreier and I. Santamaría Improper Signaling for OFDM Underlay Cognitive Radio SystemsIn Proc. IEEE Statistical Signal Processing Workshop (SSP), pp. 722-726, 2018 |
[15] |
C. Lameiro, I. Santamaria and P.J. Schreier Performance analysis of maximally improper signaling for multiple-antenna systemsIn Proc. IEEE Wireless Comm. Networking Conf. (WCNC), 2018 |
[16] |
A. Eguizabal and P.J. Schreier A weighting strategy for Active Shape ModelsIn IEEE International Conference on Image Processing 2017, 2017 |
[17] |
S. Horstmann, D. Ramírez and P.J. Schreier Detection of almost-cyclostationarity: An approach based on a multiple hypothesis testIn Proc. Asilomar Conf. Signals Syst. Computers, pp. 1635-1639, 2017 |
[18] |
C. Lameiro and P. J. Schreier A sparse CCA algorithm with application to model-order selection for small sample supportIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., pp. 4721-4725, 2017 |
[19] |
T. Hasija, Y. Song, P.J. Schreier and D. Ramírez Bootstrap-based detection of the number of signals correlated across multiple data setsIn Proc. Asilomar Conf. Signals Syst. Computers, 2016 |
[20] |
C. Lameiro, I. Santamaría, W. Utschick and P.J. Schreier Maximally improper interference in underlay cognitive radio networksIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., 2016 |
[21] |
Y. Song, T. Hasija, P.J. Schreier and D. Ramírez Determining the number of signals correlated across multiple data sets for small sample supportIn Proc. Eur. Signal Process. Conf., 2016 |
[22] |
T. Hasija, Y. Song, P.J. Schreier and D. Ramírez Detecting the dimension of the subspace correlated across multiple data sets in the sample poor regimeIn Proc. IEEE Work. Stat. Signal Process., 2016 |
[23] |
Aaron Pries, David Ramírez and Peter J. Schreier Detection of cyclostationarity in the presence of temporal or spatial structure with applications to cognitive radioIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., pp. 4249-4253, 2016 |
[24] |
J. Tong, Q. Guo, J. Xi, Y. Yu and P.J. Schreier Choosing the diagonal loading factor for linear signal estimation using cross validationIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., 2016 |
[25] |
M. Rezaee, P. J. Schreier, M. Guillaud and B. Clerckx A simple DoF-achievable scheme for the Gaussian interference channel with delayed CSITIn Proc. IEEE Global Communications Convference: Communication Theory, 2015 |
[26] |
C. Lameiro, I. Santamaría and P.J. Schreier Analysis of maximally improper signalling schemes for underlay cognitive radioIn Proc. IEEE Int. Conf. Comm., 2015 |
[27] |
D. Ramírez, P. J. Schreier, J. Vía, I. Santamaría and L. L. Scharf An asymptotic LMPI test for cyclostationarity detection with application to Cognitive Radio (invited paper)In Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., 2015 |
[28] |
N. Roseveare and P. J. Schreier Model-order selection for analyzing correlation between two data sets using CCA with PCA preprocessingIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., 2015 |
[29] |
Y. Song, P. J. Schreier and N. Roseveare Determining the number of correlated signals between two data sets using PCA-CCA when sample support is extremely smallIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., 2015 |
[30] |
D. Ramírez, P. J. Schreier, J. Vía, I. Santamaría and L. L. Scharf A Regularized Maximum Likelihood Estimator for the Period of a Cyclostationary ProcessIn Proc. Asilomar Conf. Signals Syst. Computers, 2014 |
[32] |
J. Tong, Q. Guo, P.J. Schreier and J. Xi Regularized successive interference cancellation (SIC) under mismatched modelingIn Proc. IEEE Work. Stat. Signal Process., 2014 |
[33] |
D. Ramírez, L. L. Scharf, J. Vía, I. Santamaría and P. J. Schreier An asymptotic GLRT for the detection of cyclostationary signalsIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., 2014 |
[34] |
J. Tong and P.J. Schreier Linear equalization in communications with mismatched modeling using Krylov subspace expansionIn Proc. IEEE Wireless Comm. Networking Conf. (WCNC), 2013 |
[35] |
D. Ramírez, P. J. Schreier, J. Vía and V. V. Nikulin Power-CCA: Maximizing the Correlation Coefficient between the Power of ProjectionsIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., 2013 |
[36] |
D. Ramírez, P. J. Schreier, J. Vía and I. Santamaría GLRT For Testing Separability Of A Complex-Valued Mixture Based On The Strong Uncorrelating TransformIn Proc. IEEE Int. Work. Machine Learning for Signal Process., 2012 |
[37] |
S. C. Olhede, D. Ramírez and P. J. Schreier The Random Monogenic SignalIn Proc. IEEE Int. Conf. Image Process., 2012 |
[38] |
J. Tong and P.J. Schreier Regularized linear equalization for multipath channels with imperfect channel estimationIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., pp. 3009-3012, 2012 |
[39] |
J. Tong, P.J. Schreier and S.R. Weller Precoder design and convergence analysis of MIMO systems with Krylov subspace receiversIn Proc. IEEE Int. Symp. Inform. Theory, pp. 2914-2918, 2011 |
[40] |
J. Tong, P.J. Schreier, S.R. Weller and L.L. Scharf Linear precoding for time-varying MIMO channels with low-complexity receiversIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., pp. 3092-3095, 2011 |
[41] |
P. Wahlberg and P.J. Schreier The Wiener filter for locally stationary stochastic processes is rarely locally stationaryIn Proc. 17th European Signal Process. Conf., pp. 2465-2469, 2009 |
[42] |
P.J. Schreier, T. Adali and L.L. Scharf On ICA of improper and noncircular sourcesIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., pp. 3561-3564, 2009 |
[43] |
P. Wahlberg and P.J. Schreier A time-frequency formula for LMMSE filters for nonstationary underspread continuous-time stochastic processesIn Proc. 16th European Signal Process. Conf., 2008 |
[44] |
P.J. Schreier The degree of impropriety (noncircularity) of complex random vectorsIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., pp. 3909-3912, 2008 |
[45] |
V.D. Trajkovic, M. Fu and P.J. Schreier Near-capacity turbo equalization using optimized turbo codesIn Proc. Australasian Telecomm. Netw. Applic. Conf., pp. 480-484, 2007 |
[46] |
P.J. Schreier Correlation Coefficients for Complex Random VectorsIn Proc. 41st Asilomar Conf. Signals Syst. Computers, pp. 577-581, 2007 |
[47] |
P. Wahlberg and P.J. Schreier Frequency-domain properties of locally stationary improper second-order stochastic processesIn Proc. 41st Asilomar Conf. Signals Syst. Computers, pp. 1093-1097, 2007 |
[48] |
V.D. Trajkovic, M. Fu and P.J. Schreier Turbo Equalization With Irregular Turbo CodesIn Proc. 4th Int. Symp. Wireless Comm. Syst., pp. 153-157, 2007 |
[49] |
P. Wahlberg and P.J. Schreier Spectra of multidimensional complex improper (almost) cyclostationary processesIn Proc. IEEE Int. Symp. Inform. Theory, pp. 971-975, 2007 |
[50] |
P.J. Schreier A New Interpretation of Bilinear Time-Frequency DistributionsIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., vol. 3, pp. 1133-1136, 2007 |
[51] |
M.S. Spurbeck, P.J. Schreier and L.L. Scharf Causal cyclic Wiener filteringIn Proc. 40th Asilomar Conf. Signals Syst. Computers, pp. 1425-1429, 2006 |
[52] |
P.J. Schreier, L.L. Scharf and A. Hanssen A Statistical Test for Impropriety of Complex Random SignalsIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., vol. 3, pp. 796-799, 2006 |
[53] |
P.J. Schreier, L.L. Scharf and A. Hanssen A geometric interpretation of the Rihaczek time-frequency distribution for stochastic signalsIn Proc. IEEE Int. Symp. Inform. Theory, pp. 966-969, 2005 |
[54] |
P.J. Schreier A note on aliasing in higher order spectraIn Proc. 6th Australian Comm. Theory Works., pp. 184-188, 2005 |
[55] |
P.J. Schreier and L.L. Scharf Polyspectra of analytic signalsIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., vol. 2, pp. 473-476, 2004 |
[56] |
T. McWhorter and P.J. Schreier Widely-linear beamformingIn Proc. 37th Asilomar Conf. Signals Syst. Computers, vol. 1, pp. 753-759, 2003 |
[57] |
P.J. Schreier, L.L. Scharf, T. Hu and S.D. Voran Canonical coordinates are the right coordinate system for transform coding of noisy sourcesIn Proc. IEEE Works. Statistical Signal Proces., pp. 234-237, 2003 |
[58] |
P.J. Schreier, L.L. Scharf and C.T. Mullis A unified approach to performance comparisons between linear and widely linear processingIn Proc. IEEE Works. Statistical Signal Proces., pp. 114-117, 2003 |
[59] |
P.J. Schreier and L.L. Scharf The Karhunen-Loève expansion of improper complex random signals with applications in detectionIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., vol. 6, pp. 717-720, 2003 |
[60] |
P.J. Schreier and L.L. Scharf Reducing interference in stochastic time-frequency analysis without losing informationIn Proc. 36th Asilomar Conf. Signals Syst. Computers, vol. 2, pp. 1565-1570, 2002 |
[61] |
P.J. Schreier and L.L. Scharf Canonical coordinates for reduced-rank estimation of improper complex random vectorsIn Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., vol. 2, pp. 1153-1156, 2002 |
[62] |
P.J. Schreier and L.L. Scharf Low-rank approximation of improper complex random vectorsIn Proc. 35th Asilomar Conf. Signals Syst. Computers, vol. 1, pp. 597-601, 2001 |
[63] |
P.J. Schreier and J. Costello MAP decoding of linear block codes based on a sectionalized trellis of the dual codeIn Proc. Int. Zurich Seminar Broadband Comm., pp. 271-278, 2000 |