Results 251 to 260 of about 166,858,438 (333)
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IEEE Transactions on Systems, Man, and Cybernetics, 1971
Lainiotis, D. G., Park, S. K.
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Lainiotis, D. G., Park, S. K.
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AEU - International Journal of Electronics and Communications, 2019
The present work covers the wide range of distributions and proposes the moment generating function (MGF) based analytical framework to derive the average symbol error probability (SEP), the average probability of detection (PD), and the average area ...
P. S. Chauhan, Sandeep Kumar, S. Soni
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The present work covers the wide range of distributions and proposes the moment generating function (MGF) based analytical framework to derive the average symbol error probability (SEP), the average probability of detection (PD), and the average area ...
P. S. Chauhan, Sandeep Kumar, S. Soni
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Uncertainty and the probability of error (Corresp.)
IEEE Transactions on Information Theory, 1968D. Tebbe, Samuel J. Dwyer III
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Philosophy of Science, 1997
The Bayesian theory is outlined and its status as a logic defended. In this it is contrasted with the development and extension of Neyman-Pearson methodology by Mayo in her recently published book (1996). It is shown by means of a simple counterexample that the rule of inference advocated by Mayo is actually unsound.
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The Bayesian theory is outlined and its status as a logic defended. In this it is contrasted with the development and extension of Neyman-Pearson methodology by Mayo in her recently published book (1996). It is shown by means of a simple counterexample that the rule of inference advocated by Mayo is actually unsound.
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IEEE Transactions on Communications, 1999
Summary: This paper presents new forms for an error probability associated with the phase angle between two vectors perturbed by Gaussian noise. An interesting consequence of the underlying generic form is a new expression for the symbol error rate in MDPSK that is very similar to its counterpart for MPSK. The generic error probability is further shown
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Summary: This paper presents new forms for an error probability associated with the phase angle between two vectors perturbed by Gaussian noise. An interesting consequence of the underlying generic form is a new expression for the symbol error rate in MDPSK that is very similar to its counterpart for MPSK. The generic error probability is further shown
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On the estimation of probability of error
1974 IEEE Conference on Decision and Control including the 13th Symposium on Adaptive Processes, 1974This paper considers the problem of estimation of classification error in Pattern Recognition. A Theorem is presented to obtain the changes in the eigenvalues and eigenvectors of matrices of the form S2 -1 S1, when there are changes of first order of smallness in the real Symmetric matrices Si, i=1, 2.
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Problems of Information Transmission, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rossitza Dodunekova +1 more
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rossitza Dodunekova +1 more
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Measurement Errors in Probability Judgments
Management Science, 1996This paper investigates the psychometric properties of three measures of subjective uncertainty—a zero-to-hundred subjective probability scale and two seven point rating scales. Individual level analysis applied to data obtained from two separate studies suggests that the scales produce fairly similar results: The inter-response mode correlations were
OFIR, Chezy, REDDY, Srinivas K.
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Intersymbol interference and error probability
IEEE Transactions on Information Theory, 1966Using a criterion of minimum average error probability we derive a method for specifying an optimum linear, time invariant receiving filter for a digital data transmission system. The transmitted data are binary and coded into pulses of shape \pm s(t) .
M. R. Aaron, Donald W. Tufts
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Conditional entropy and error probability
2008 IEEE International Symposium on Information Theory, 2008Fano's inequality relates the error probability and conditional entropy of a finitely-valued random variable X given another random variable Y. It is not necessarily tight when the marginal distribution of X is fixed. In this paper, we consider both finite and countably infinite alphabets.
Siu-Wai Ho, Sergio Verdú
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