Adaptive soft-constraint satisfaction (SCS) algorithms for fractionally-spaced blind equalizers

被引：0
|
作者：
Baykal, B
Tanrikulu, O
Chambers, JA
机构：
来源：
1997 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I - V: VOL I: PLENARY, EXPERT SUMMARIES, SPECIAL, AUDIO, UNDERWATER ACOUSTICS, VLSI; VOL II: SPEECH PROCESSING; VOL III: SPEECH PROCESSING, DIGITAL SIGNAL PROCESSING; VOL IV: MULTIDIMENSIONAL SIGNAL PROCESSING, NEURAL NETWORKS - VOL V: STATISTICAL SIGNAL AND ARRAY PROCESSING, APPLICATIONS | 1997年
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中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
Constant Modulus algorithms based on a deterministic error criterion are presented. Soft constraint satisfaction methods yield a general family of blind equalization algorithms employing nonlinear functions of the equalizer output which must satisfy certain conditions. The algorithms are also extended to cover fractionally-spaced blind equalization. A normalization factor which appears as a result of the deterministic formulation of the problem helps the blind equalizer improve its performance. Also, the family supports a wide range of nonlinear functions. Extensive simulations are presented to reveal convergence characteristics which also include signals from the Signal Processing Information Base (SPIB).
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页码：1853 / 1856
页数：4
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