Address

Dept. of Electrical Engineering and Information Technology (EIM-E)
Paderborn University
33098 Paderborn, Germany

Contact Information

Call: +49 (5251) 60-2213

Email: peter.schreier@sst.upb.de

Room: P1.7.01.2

Professor Peter Schreier

Dean, Faculty of Electrical Engineering, Computer Science, and Mathematics
and Chair Professor

Signal and System Theory Group

Biography

I was born in Munich, Germany, in 1975. I received a Master of Science from the University of Notre Dame, Indiana, USA, in 1999, and a Ph.D. from the University of Colorado at Boulder, USA, in 2003, both in electrical engineering. In the Fall semester of 1998, I was a visiting research student with the Coding Group at the University of Hawaii at Manoa, USA.

From 2004 until 2011, I was with the School of Electrical Engineering and Computer Science at the University of Newcastle, Australia, first as Lecturer, then Senior Lecturer, and finally Associate Professor. In the Spring semester of 2008, I was a Visiting Associate Professor with the Department of Electrical and Computer Engineering at Colorado State University, Ft. Collins, USA.

Since 2011, I have been Professor and Head of the Signal and System Theory Group, and in 2019, I was elected Dean of the Faculty of Electrical Engineering, Computer Science & Mathematics at the University of Paderborn, Germany. In 2018, I co-founded metamorphosis, which is a spin-off startup developing AI-based technologies for computer-assisted musculoskeletal surgery, and I have since served as its Chief Executive Officer.

I have received fellowships from the State of Bavaria, the Studienstiftung des deutschen Volkes (German National Academic Foundation), and the Deutsche Forschungsgemeinschaft (German Research Foundation).

From 2008 until 2012, I was an Associate Editor of the IEEE Transactions on Signal Processing, from 2010 until 2014 a Senior Area Editor for the IEEE Transactions on Signal Processing, and from 2015 to 2018 an Associate Editor for the IEEE Signal Processing Letters. I was the General Chair of the 2018 IEEE Statistical Signal Processing Workshop in Freiburg, Germany. From 2009 until 2014, I was a member of the IEEE Technical Committee on Machine Learning for Signal Processing, and from 2016 until 2021, a member of the IEEE Technical Committee on Signal Processing Theory and Methods. I am a Past Chair (2019-20) and currently Vice Chair of the Steering Committee of the IEEE Signal Processing Society’s (SPS) Data Science Initiative.

Current Appointments

  1. since 2019

    Dean of Electrical Engineering, Computer Science & Mathematics

    Paderborn University

  2. since 2018

    Chief Executive Officer

    metamorphosis GmbH

  3. since 2011

    Chair Professor of Signal and System Theory

    Paderborn University

Professional Service Highlights

  • Chair of the Steering Committee
    2019-20
    IEEE Signal Processing Society (SPS) Data Science Initiative
  • Member
    2019-20
    Technical Directions Board of IEEE SPS
  • General Chair
    2018
    IEEE Workshop on Statistical Signal Processing, Freiburg
  • Senior Area Editor
    2010-14
    IEEE Transactions on Signal Processing
  • Associate Editor
    2008-12
    IEEE Transactions on Signal Processing
  • Associate Editor
    2015-18
    IEEE Signal Processing Letters

List of Publications

Books

[1]

P.J. Schreier and L.L. Scharf

Statistical Signal Processing of Complex-Valued Data: The Theory of Improper and Noncircular Signals

330 pages, Cambridge University Press, 2010

Journal Articles

[1]

M. Soleymani, I. Santamaria and P.J. Schreier

Improper Gaussian Signaling for the K-User MIMO Interference Channels With Hardware Impairments

IEEE Transactions on Vehicular Technology, vol. 69, no. 10, pp. 11632-11645, IEEE, 2020
[2]

T. Hasija, T. Marrinan, C. Lameiro and P.J. Schreier

Determining the dimension and structure of the subspace correlated across multiple data sets

Signal Processing, vol. 176, Elsevier, 2020
[3]

S. Horstmann, D. Ramírez and P.J. Schreier

Two-channel passive detection of cyclostationary signals

IEEE Transactions on Signal Processing, vol. 68, no. 1, pp. 2340-2355, IEEE, 2020
[4]

C. Lameiro, I. Santamaría, P.J. Schreier and W. Utschick

Maximally Improper Signaling in Underlay MIMO Cognitive Radio Networks

IEEE Transactions on Signal Processing, vol. 67, no. 24, pp. 6241-6255, IEEE, 2019
[5]

M. Soleymani, C. Lameiro, I. Santamaria and P.J. Schreier

Improper Signaling for SISO Two-user Interference Channels with Additive Asymmetric Hardware Distortion

IEEE Trans. Commun., IEEE, 2019
[6]

M. Soleymani, C. Lameiro, I. Santamaria and P.J. Schreier

Robust Improper Signaling for Two-user SISO Interference Channels

IEEE Trans. Commun., vol. 67, no. 7, pp. 4709-4723, IEEE, 2019
[7]

M. Soleymani, I. Santamaria, C. Lameiro and P.J. Schreier

Ergodic Rate for Fading Interference Channels with Proper and Improper Gaussian Signaling

Entropy, vol. 21, no. 10, pp. 922, Multidisciplinary Digital Publishing Institute, 2019
[8]

S. Vieluf, T. Hasija, R. Jakobsmeyer, P.J. Schreier and C. Reinsberger

Exercise-induced changes of multimodal interactions within the autonomic nervous network

Frontiers in physiology, vol. 10, Frontiers, 2019
[9]

S. Vieluf, V. Scheer, T. Hasija, P.J. Schreier and C. Reinsberger

Multimodal approach towards understanding the changes in the autonomic nervous system induced by an ultramarathon

Research in Sports Medicine, pp. 1-10, Taylor & Francis, 2019
[10]

A. Eguizabal, C. Lameiro, D. Ramirez and P. J. Schreier

Source enumeration in the presence of colored noise

IEEE Signal Proc. Lett., vol. 26, no. 3, pp. 475-479, 2019
[11]

C. Lameiro, I. Santamaría and P.J. Schreier

Improper Gaussian signaling for multiple-access channels in underlay cognitive radio

IEEE Transactions on Communications, vol. 67, no. 3, pp. 1817-1830, IEEE, 2018, (Available at https://arxiv.org/abs/1711.09768).
[12]

I. Santamaria, P.M. Crespo, C. Lameiro and P.J. Schreier

Information-Theoretic Analysis of a Family of Improper Discrete Constellations

Entropy, vol. 20, no. 1, 2018
[13]

S. Horstmann, D. Ramírez and P.J. Schreier

Joint Detection of Almost-Cyclostationary Signals and Estimation of Their Cycle Period

IEEE Signal Process. Lett., vol. 25, no. 11, pp. 1695-1699, 2018
[14]

Aaron Pries, David Ramírez and Peter J. Schreier

LMPIT-inspired Tests for Detecting a Cyclostationary Signal in Noise with Spatio-Temporal Structure

IEEE Trans. Wirel. Commun., vol. 17, no. 9, pp. 6321-6334, 2018, (Available at https://arxiv.org/abs/1803.08791).
[15]

M. Rezaee and P.J. Schreier

A degrees-of-freedom-achieving scheme for the temporally correlated MIMO interference channel with delayed CSIT

IEEE Trans. Wireless Comm., vol. 17, no. 8, pp. 5397-5408, 2018
[16]

T. Hasija, C. Lameiro and P.J. Schreier

Determining the dimension of the improper signal subspace in complex-valued data

IEEE Signal Process. Lett., vol. 24, pp. 1606-1610, 2017
[17]

C. Lameiro, I. Santamaría and P.J. Schreier

Rate region boundary of the SISO Z-interference channel with improper signaling

IEEE Trans. Comm., vol. 65, no. 3, pp. 1022-1034, 2017
[18]

Y. Song, P.J. Schreier, D. Ramírez and T. Hasija

Canonical correlation analysis of high-dimensional data with very small sample support

Signal Process., vol. 128, pp. 449-458, 2016
[19]

Y. Levin-Schwartz, Y. Song, P.J. Schreier, V. Calhoun and T. Adali

Sample-poor estimation of order and common signal subspace with application to fusion of medical imaging data

NeuroImage, vol. 134, pp. 486-493, 2016
[20]

J. Tong, P.J. Schreier, Q. Guo, S. Tong, J. Xi and Y. Yu

Shrinkage of covariance matrices for linear signal estimation using cross-validation

IEEE Trans. Signal Process., vol. 64, no. 11, pp. 2965-2975, 2016
[21]

M. Rezaee, P.J. Schreier, M. Guillaud and B. Clerckx

A unified scheme to achieve the degrees-of-freedom region of the MIMO interference channel with delayed channel state information

IEEE Trans. Comm., vol. 64, no. 3, pp. 1068-1082, 2016
[22]

D. Ramírez, P. J. Schreier, J. Via, I. Santamaria and L. L. Scharf

Detection of multivariate cyclostationarity

IEEE Trans. Signal Processing, vol. 63, no. 20, pp. 5395-5408, 2015
[23]

C. Lameiro, I. Santamaría and P.J. Schreier

Benefits of Improper Signaling for Underlay Cognitive Radio

IEEE Wireless Comm. Lett., vol. 4, pp. 22-25, 2015
[24]

S. Dähne, V. V. Nikulin, D. Ramírez, P. J. Schreier, K.-R. Müller and S. Haufe

Finding brain oscillations with power dependencies in neuroimaging data

NeuroImage, vol. 96, pp. 334-348, 2014
[25]

S. C. Olhede, D. Ramírez and P. J. Schreier

Detecting Directionality in Random Fields Using the Monogenic Signal

IEEE Trans. Inform. Theory, vol. 60, no. 10, pp. 6491-6510, 2014
[26]

T. Adali and P.J. Schreier

Optimization and estimation of complex-valued signals

IEEE Signal Processing Magazine, vol. 31, no. 5, pp. 112-128, 2014
[27]

D. Ramírez, P. J. Schreier, J. Vía and I. Santamaría

Testing blind separability of complex Gaussian mixtures

Signal Process., vol. 95, pp. 49-57, 2014
[28]

P.J. Schreier

Neue Anwendungsgebiete für Computer Assisted Surgery (CAS)

ForschungsForum Paderborn, vol. 17, pp. 24-30, 2014
[29]

J. Tong and P.J. Schreier

A unified framework for regularized linear estimation in communication systems

Signal Process., vol. 93, no. 9, pp. 2671-2686, 2013
[30]

J. Tong and P.J. Schreier

Regularized Preconditioning for Krylov Subspace Equalization of OFDM Systems over Doubly Selective Channels

IEEE Wireless Comm. Lett., vol. 2, no. 4, pp. 367-370, 2013
[31]

P. Wahlberg and P.J. Schreier

On the instantaneous frequency of Gaussian stochastic processes

Probab. Math. Statist., vol. 32, pp. 69-92, 2012
[32]

J. Tong, P.J. Schreier and S.R. Weller

Linear precoding for MIMO systems with low-complexity receivers

IEEE Trans. Wireless Comm., vol. 11, no. 8, pp. 2828-2837, 2012
[33]

J. Tong, P.J. Schreier and S.R. Weller

Design and analysis of large MIMO systems with Krylov subspace receivers

IEEE Trans. Signal Process., vol. 60, no. 5, pp. 2482-2493, 2012
[34]

P. Wahlberg and P.J. Schreier

Locally stationary harmonizable complex improper stochastic processes

J. Time Ser. Anal., vol. 32, no. 1, pp. 33-46, Blackwell Publishing Ltd, 2011
[35]

T. Adali, P.J. Schreier and L.L. Scharf

Complex-Valued Signal Processing: The Proper Way to Deal With Impropriety

IEEE Trans. Signal Process., vol. 59, no. 11, pp. 5101-5125, 2011
[36]

P. Wahlberg and P.J. Schreier

On Wiener filtering of certain locally stationary stochastic processes

Signal Process., vol. 90, no. 3, pp. 885-890, 2010
[37]

P. Wahlberg and P.J. Schreier

Gabor discretization of the Weyl product for modulation spaces and filtering of nonstationary stochastic processes

Appl. Comput. Harmon. Anal., vol. 26, no. 1, pp. 97-120, 2009
[38]

P.J. Schreier

Bounds on the Degree of Impropriety of Complex Random Vectors

IEEE Signal Process. Lett., vol. 15, pp. 190-193, 2008
[39]

P.J. Schreier

Polarization Ellipse Analysis of Nonstationary Random Signals

IEEE Trans. Signal Process., vol. 56, no. 9, pp. 4330-4339, 2008
[40]

P.J. Schreier

A Unifying Discussion of Correlation Analysis for Complex Random Vectors

IEEE Trans. Signal Process., vol. 56, no. 4, pp. 1327-1336, 2008
[41]

P. Wahlberg and P.J. Schreier

Spectral Relations for Multidimensional Complex Improper Stationary and (Almost) Cyclostationary Processes

IEEE Trans. Inform. Theory, vol. 54, no. 4, pp. 1670-1682, 2008
[42]

M.S. Spurbeck and P.J. Schreier

Causal Wiener filter banks for periodically correlated time series

Signal Process., vol. 87, no. 6, pp. 1179-1187, Elsevier North-Holland, Inc., 2007
[43]

P.J. Schreier and L.L. Scharf

Higher-order spectral analysis of complex signals

Signal Process., vol. 86, no. 11, pp. 3321-3333, 2006
[44]

P.J. Schreier, L.L. Scharf and A. Hanssen

A generalized likelihood ratio test for impropriety of complex signals

IEEE Signal Process. Lett., vol. 13, no. 7, pp. 433-436, 2006
[45]

P.J. Schreier and L.L. Scharf

Canonical coordinates for transform coding of noisy sources

IEEE Trans. Signal Process., vol. 54, no. 1, pp. 235-243, 2006
[46]

L.L. Scharf, P.J. Schreier and A. Hanssen

The Hilbert space geometry of the Rihaczek distribution for stochastic analytic signals

IEEE Signal Process. Lett., vol. 12, no. 4, pp. 297-300, 2005
[47]

P.J. Schreier, L.L. Scharf and C.T. Mullis

Detection and estimation of improper complex random signals

IEEE Trans. Inform. Theory, vol. 51, no. 1, pp. 306-312, 2005
[48]

P.J. Schreier and L.L. Scharf

Stochastic time-frequency analysis using the analytic signal: why the complementary distribution matters

IEEE Trans. Signal Process., vol. 51, no. 12, pp. 3071-3079, 2003
[49]

P.J. Schreier and L.L. Scharf

Second-order analysis of improper complex random vectors and processes

IEEE Trans. Signal Process., vol. 51, no. 3, pp. 714-725, 2003

Conference Articles

[1]

M. Soleymani, I. Santamaria, B. Maham and P.J. Schreier

Rate Region of the K-user MIMO Interference Channel with Imperfect Transmitters

In 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 Populations

In 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 Noise

In 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 Networks

In Proc. Asilomar Conf. on Signals, Systems, Computers, 2019
[5]

S. Horstmann, D. Ramírez and P.J. Schreier

Two-channel passive detection exploiting cyclostationarity

In 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 Projections

In 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 Radio

In 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 structure

In 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 Channels

In 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 Signaling

In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4769-4773, 2019
[11]

A. Eguizabal, P. J. Schreier and D. Ramírez

MODEL-ORDER SELECTION IN STATISTICAL SHAPE MODELS

In 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 Analysis

In 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 detection

In 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 Systems

In 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 systems

In Proc. IEEE Wireless Comm. Networking Conf. (WCNC), 2018
[16]

A. Eguizabal and P.J. Schreier

A weighting strategy for Active Shape Models

In 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 test

In 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 support

In 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 sets

In 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 networks

In 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 support

In 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 regime

In 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 radio

In 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 validation

In 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 CSIT

In 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 radio

In 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 preprocessing

In 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 small

In 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 Process

In Proc. Asilomar Conf. Signals Syst. Computers, 2014
[31]

S. Dähne, V. V. Nikulin, D. Ramírez, P. J. Schreier, K.-R. Müller and S. Haufe

Optimizing spatial filters for the extraction of envelope-coupled neural oscillations

In Proc. Int. Work. Pattern Recognition In Neuroimaging, 2014
[32]

J. Tong, Q. Guo, P.J. Schreier and J. Xi

Regularized successive interference cancellation (SIC) under mismatched modeling

In 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 signals

In 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 expansion

In 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 Projections

In 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 Transform

In Proc. IEEE Int. Work. Machine Learning for Signal Process., 2012
[37]

S. C. Olhede, D. Ramírez and P. J. Schreier

The Random Monogenic Signal

In Proc. IEEE Int. Conf. Image Process., 2012
[38]

J. Tong and P.J. Schreier

Regularized linear equalization for multipath channels with imperfect channel estimation

In 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 receivers

In 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 receivers

In 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 stationary

In 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 sources

In 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 processes

In Proc. 16th European Signal Process. Conf., 2008
[44]

P.J. Schreier

The degree of impropriety (noncircularity) of complex random vectors

In 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 codes

In Proc. Australasian Telecomm. Netw. Applic. Conf., pp. 480-484, 2007
[46]

P.J. Schreier

Correlation Coefficients for Complex Random Vectors

In 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 processes

In 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 Codes

In 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 processes

In Proc. IEEE Int. Symp. Inform. Theory, pp. 971-975, 2007
[50]

P.J. Schreier

A New Interpretation of Bilinear Time-Frequency Distributions

In 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 filtering

In 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 Signals

In 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 signals

In Proc. IEEE Int. Symp. Inform. Theory, pp. 966-969, 2005
[54]

P.J. Schreier

A note on aliasing in higher order spectra

In Proc. 6th Australian Comm. Theory Works., pp. 184-188, 2005
[55]

P.J. Schreier and L.L. Scharf

Polyspectra of analytic signals

In Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., vol. 2, pp. 473-476, 2004
[56]

T. McWhorter and P.J. Schreier

Widely-linear beamforming

In 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 sources

In 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 processing

In 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 detection

In 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 information

In 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 vectors

In Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process., vol. 2, pp. 1153-1156, 2002
[62]

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