Hypothesis Testing and Identification Systems

Abstract

We study hypothesis testing problems with fixed compression mappings and with user-dependent compression mappings to decide whether or not an observation sequence is related to one of the users in a database, which contains compressed versions of previously enrolled users' data. We first provide the optimal characterization of the exponent of the probability of the second type of error for the fixed compression mappings scenario when the number of users in the database grows exponentially. We then establish operational equivalence relations between the Wyner-Ahlswede-Körner network, the single-user hypothesis testing problem, the multi-user hypothesis testing problem with userdependent compression mappings and the identification systems with user-dependent compression mappings. These equivalence relations imply the strong converse and exponentially strong converse for the multi-user hypothesis testing and the identification systems both with user-dependent compression mappings. Finally they also show how an identification scheme can be turned into a multi-user hypothesis testing scheme with an explicit transfer of rate and error probability conditions and vice versa.

An intelligent ubiquitous compression technique for DNA sequencing using Hadoop

“…The algorithm takes the transcription factor of $$p \le 0.05$$ as the activating transcription factor. Then perform the following DNA sequence compression operation [31].…”

A QoS Classifier Based on Machine Learning for Next-Generation Optical Communication

“…This is shown by the p-value, which is the degree of marginal significance in a statistical hypothesis test and represents the likelihood that a particular event will occur. To assess if there is a significant difference between the means of the two groups, which may be connected in certain attributes, the t-test is a common sort of inferential statistic [11]. The two groups in this case are the population and the sample for Q-factor, SNR and BER.…”

Uncertainty in Biometric Identification and Authentication Systems with Strong Secrecy

“…The study of biometric identification and authentication has been developed in many perspectives. For example, the privacy and secrecy aspects are studied in [1]- [5]; hierarchical identification is studied in [6]- [8]; hypothesis testing in identification is considered in [9]; fundamental limits-achieving code designs are studied in [10], [11]. In the aforementioned literature, it is assumed that the probability mass function of the biometrics and the channels are fixed.…”