Information-theoretic Measures Of Uncertainty Research Articles

Insights into codeswitching from online communication: Effects of language preference and conditions arising from vocabulary richness

AbstractTwitter data from a crisis that impacted many English–Spanish bilinguals show that the direction of codeswitches is associated with the statistically documented tendency of single speakers to prefer one language over another in their tweets, as gleaned from their tweeting history. Further, lexical diversity, a measure of vocabulary richness derived from information-theoretic measures of uncertainty in communication, is greater in proximity to a codeswitch than in productions remote from a switch. The prospects of a role for lexical diversity in characterizing the conditions for a language switch suggest that communicative precision may induce conditions that attenuate constraints against language mixing.

Information theoretic measures of uncertainty of a noncommutative anisotropic oscillator in a homogeneous magnetic field

A noncommutative anisotropic oscillator in the presence of a homogeneous magnetic field is studied and the Schrödinger equation is solved analytically. We evaluated various information theoretic measures of uncertainty e.g., Heisenberg uncertainty relation, Shannon area and Fisher area for several states, including the ground state. It has been shown that the ground state is coherent for different magnetic fields. The optimum values of the Shannon area have found in position and momentum spaces. We observe that the Fisher area in momentum space has a maximum value without a magnetic field. Bialynicki–Birula–Mycielski (BBM) and Cramer–Rao uncertainty relations have been verified.

The microgenesis of information acquisition in visual ‘popout’

Visual popout refers to searches in which one feature distinguishes a target and time to detection is relatively unaffected by number of nontargets. Rapid detection can make it seem like information about a target is obtained immediately and passively. We sought to investigate the acquisition of target-related information in the earliest moments of a search. In Experiment 1 a color-singleton display was masked after a 16.7-900 ms exposure, and the task was to click the position that the target occupied. We translated average response-distance-error into entropy, an information-theoretic measure of uncertainty. We could thus ask how much increasing exposure reduces uncertainty about a target's position. In the first 200ms, uncertainty declined linearly, then plateauing (reflecting perceptual and motor precision). We fit two continuous time models to the responses of each participant, one characterizing a passive strategy of estimating an item's position successively from received signals, the other, a more active strategy of querying whether a signal is present in successively smaller portions of an image. The active model fit significantly better. In Experiment 2, we scrutinized individual differences in rate of information gain. We replicated the results of Experiment 1, accompanied by color change detection to measure working memory capacity. Rate of information gain was significantly correlated with memory capacity (r=0.55). This suggests that rate of information acquisition may underwrite broad cognitive functioning as WM capacity is known to do. Additional experiments related these results to reaction times in detection search and other forms of popout. Overall, the results suggest a new way to characterize visual search at the algorithmic level. We discuss how this algorithmic theory is consistent with psychological theories such as 'guided search,' and how it can be extended to account for inefficient conjunction search and search asymmetries. Meeting abstract presented at VSS 2015. Language: en

Information-theoretic measures associated with rough set approximations

In rough set theory, some information-theoretic measures of uncertainty and granularity have been proposed. A common feature of these measures is that they are only dependent on the partitions and the cardinality of a universe, which means that they are independent of the lower and upper approximations of rough sets. This seems somewhat unreasonable since the basic idea of rough set theory is to describe incomplete or inexact concepts by the lower and upper approximations. In light of this, we develop a new pair of information-theoretic entropy and co-entropy functions associated to partitions and approximations in this paper. Such functions are used to measure the uncertainty and granularity of an approximation space. After introducing the novel notions of entropy and co-entropy, we then examine their properties. In particular, we disclose the relationship of co-entropies between different universes. The theoretical development is accompanied by illustrative numerical examples.