摘要: We show that the normalized generalized mutual information represents an excellent forward error correction (FEC) threshold for uniform as well as for probabilistically shaped QAM and hence allows to accurately predict post-FEC performance from measured pre-FEC data....
Support Vector Machine Density Estimator as a Generalized Parzen Windows Estimator for Mutual Information based Image Registration Mutual Information is perhaps the most widely used multimodality image registration method. A crucial step in mutual information is the estimation of the probability density funct...
generalized entropiesjensen's differenceinformation theorymutual informationsimilarity measuresTwo new similarity measures for rigid image registration, based on the normalization of Jensen's difference applied to Reriyi and Tsallis-Havrda-Charvat entropies, are introduced. One measure is normalized by the...
Prototype-based minimum classification error/generalized probabilistic descent training for various speech units set task, as well as for isolated word recognition for a vocabulary of 5240 words, that reveal clear gains in performance as a result of using PBMEC... MD Katagiri - 《Computer Speech ...
Multilocus LD Measure and Tagging SNP Selection with Generalized Mutual Information Linkage disequilibrium (LD) plays a central role in fine mapping of disease genes and, more recently, in characterizing haplotype blocks. Classical LD meas... Z Liu,S Lin - 《Genetic Epidemiology》 被引量: 0发表...
We use the generalized sequence pattern, GSP [12], as the baseline for comparison on the efficiency of the M3Cap algorithm. The three core steps of GSP are (1) finding the frequent 1-items to generate one-level sequence patterns; (2) linking and pruning to generate candidate patterns; and...
The generalized sequential pattern (GSP) algorithm was then developed as an improvement [12]. Such algorithms use the core idea of Apriori and adopt the recursive linking and pruning function, which requires the repetition of database scanning to generate sequential patterns. To overcome this ...
To address this problem, the generalized divergence measure based on Renyi Entropy [17], Kullback-Leibler Divergence [18], mutual information (MI) and cross-cumulative residual entropy (CCRE) [19] have been proposed. Among these metrics, MI has been investigated in-depth and widely applied to...
Classification of normal and pre-ictal eeg signals using permutation entropies and a generalized linear model as a classifier. Entropy 2017, 19, 72. [Google Scholar] [CrossRef] Fotios, S.M. Credit market Jitters in the course of the financial crisis: A permutation entropy approach in ...