The a posteriori probability density function p(θ|X1, X2,...,Xk), where the Xi, i=1, 2, ..., K, represent Kvector-valued observations statistically related to the random vector θ, appears in many applications of the methods of statistical inference to problems in pattern recognition and statistical communication theory. In this paper, it is shown that for equally likely binary sequences (M= 2) of anticorrelated patterns for signals observed in additive Gaussian noise, a device that computes pθ|X1, X2, XK) can be synthesized from a correlator, a simple instantaneous nonlinearity, and a multiplier. These results are used to derive some equally simple structures for various optimum nonsupervised estimators, pattern recognition machines, and signal detectors.


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    Title :

    Optimum Adaptive Reception for Binary Sequences


    Contributors:


    Publication date :

    1970-05-01


    Size :

    949672 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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