Matrix analysis
Computing the polar decomposition with applications
SIAM Journal on Scientific and Statistical Computing
Generation of k-distributed random variables
Transactions of the Society for Computer Simulation International
Ten lectures on wavelets
Matrix computations (3rd ed.)
Orthogonal multiuser detection
Signal Processing
Orthogonal matched filter detection
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05
Detection of stochastic processes
IEEE Transactions on Information Theory
On quantum detection and the square-root measurement
IEEE Transactions on Information Theory
Optimal tight frames and quantum measurement
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Designing optimal quantum detectors via semidefinite programming
IEEE Transactions on Information Theory
MMSE whitening and subspace whitening
IEEE Transactions on Information Theory
An optimal whitening approach to linear multiuser detection
IEEE Transactions on Information Theory
Optimal detection of symmetric mixed quantum states
IEEE Transactions on Information Theory
Orthogonal multiuser detection
Signal Processing
A narrative approach for speech signal based MMSE estimation using quantum parameters
WSEAS Transactions on Signal Processing
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This paper considers the genetic problem of detecting in the presence of additive noise, which one from a set of known signals has been received. In place of the classical matched filter (MF) receiver we propose a modified receiver. When the transmitted signals are linearly independent this receiver is referred to as an orthogonal matched filter (OMF) receiver, and when the transmitted signals are linearly dependent it is referred to as a projected orthogonal matched filter (POMF) receiver. Two equivalent representations of the receiver are developed with different implications in terms of implementation. In the first, the demodulator consists of a MF demodulator followed by an optimal whitening transformation on a space formed by the transmitted signals, that optimally decorrelates the MF outputs prior to detection. In the second, the demodulator consists of a bank of correlators with correlating signals that are projections of a set of orthogonal signals, and are closest in a least-squares sense to the transmitted signals. We provide simulation results that suggest that in certain cases the OMF and POMF receivers can significantly increase the probability of correct detection over the MF receiver in non-Gaussian noise with only a minor impact on performance in Gaussian noise.