In a detection network, the final decision is made by fusing the decisions from local detectors. The objective of that decision is to minimize the final error probability. To implement and optimal fusion rule, the performance of each detector, i.e. its probability of false alarm and its probability of missed detection as well as the a priori probabilities of the hypotheses, must be known. How...

Since the seminal work of Gilboa and Schmeidler [28, p. 142] a relation between decision making under ambiguity and robust Bayesian statistics has been hinted at, and indeed immediate similarities are quite evident. At the same time, a formal treatment of this topic and a complete characterization of the relation between the two approaches is still missing. The object of this paper is to …ll th...

Nonadditive expected utility models were developed for explaining preferences in settings where probabilities cannot be assigned to events. In the absence of probabilities, difficulties arise in the interpretation of likelihoods of events. In this paper we introduce a notion of revealed likelihood that is defined entirely in terms of preferences and that does not require the existence of (subje...

A method to quantify the error probability at the Kirchhoff-law-Johnson-noise (KLJN) secure key exchange is introduced. The types of errors due to statistical inaccuracies in noise voltage measurements are classified and the error probability is calculated. The most interesting finding is that the error probability decays exponentially with the duration of the time window of single bit exchange...

We derive new upper bounds on the error exponents for the maximum-likelihood decoding and error detecting in the binary symmetric channels. This is an improvement on the best earlier known bounds by Shannon–Gallager–Berlekamp (1967) and McEliece–Omura (1977). For the probability of undetected error the new bounds are better than the bounds by Levenshtein (1978, 1989) and the recent bound by Abd...

In this work, we introduce the notion of the error exponent region for a multi-user channel. This region specifies the set of error-exponent vectors that are simultaneously achievable by all users in the multi-user channel. This is done by associating different probabilities of error for different users, contrary to the traditional approach where a single probability of system error is consider...

We consider a Bonferroni-type lower bound due to Kounias on the probability of a finite union. The bound is expressed in terms of only the individual and pairwise event probabilities; however, it suffers from requiring an exponentially complex search for its direct implementation. We address this problem by presenting a practical algorithm for its evaluation. This bound is applied together with...

For ordinary circuits with a xed upper bound on the maximal fanin of gates it has been shown that logarithmic redundancy is necessary and suucient to overcome random hardware faults. Here, we consider the same question for unbounded fanin circuits that in the noiseless case can compute Boolean functions in sublogarithmic depth. In this case the details of the fault model become more important. ...

Birnbaum (2011, 2012) questioned the iid (independent and identically distributed) sampling assumptions used by state-of-the-art statistical tests in Regenwetter, Dana and Davis-Stober’s (2010, 2011) analysis of the “linear order model”. Birnbaum (2012) cited, but did not use, a test of iid by Smith and Batchelder (2008) with analytically known properties. Instead, he created two new test stati...