Global minimization of large-scale constrained concave quadratic problems by separable programming
Mathematical Programming: Series A and B
An algorithm for global minimization of linearly constrained concave quadratic functions
Mathematics of Operations Research
Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Interior point algorithms: theory and analysis
Interior point algorithms: theory and analysis
SIAM Journal on Scientific Computing
SIAM Journal on Optimization
Blind channel identification based on second order cyclostationary statistics
ICASSP '93 Proceedings of the Acoustics, Speech, and Signal Processing, 1993. ICASSP-93 Vol 4., 1993 IEEE International Conference on - Volume 04
A blind source separation technique using second-order statistics
IEEE Transactions on Signal Processing
Blind fractionally spaced equalization of noisy FIR channels: direct and adaptive solutions
IEEE Transactions on Signal Processing
Blind digital signal separation using successive interferencecancellation iterative least squares
IEEE Transactions on Signal Processing
General approach to blind source separation
IEEE Transactions on Signal Processing
A fractionally spaced blind equalizer based on linear programming
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
On convergence analysis of fractionally spaced adaptive blindequalizers
IEEE Transactions on Signal Processing
Blind constant modulus equalization via convex optimization
IEEE Transactions on Signal Processing
Maximum likelihood parameter and rank estimation in reduced-rankmultivariate linear regressions
IEEE Transactions on Signal Processing
Blind adaptive multiuser detection
IEEE Transactions on Information Theory
Blind system identification using precise and quantized observations
Automatica (Journal of IFAC)
Hi-index | 35.69 |
Blind equalization and signal separation are two well-established signal processing problems. In this paper, we present a quadratic programming algorithm for fast blind equalization and signal separation. By introducing a special non-mean-square error (MSE) objective function, we reformulate fractionally spaced blind equalization into an equivalent quadratic programming problem. Based on a clear geometric interpretation and a formal proof, we show that a perfect equalization solution is obtained at every local optimum of the quadratic program. Because blind source separation is, by nature and mathematically, a closely related problem, we also generalize the algorithm for blind signal separation. We show that by enforcing source orthogonalization through successive processing, the quadratic programming approach can be applied effectively. Moreover, the quadratic program is easily extendible to incorporate additional practical conditions, such as jamming suppression constraints. We also provide evidence of good performance through computer simulations.