This article examines the problem of specification error in 2 models for categorical latent variables; the latent class model and the latent Markov model. Specification error in the latent class model focuses on the impact of incorrectly specifying the number of latent classes of the categorical latent variable on measures of model adequacy as well as sample reallocation to latent classes. The ...

Most recent works on soft errors only address circuit reliability under single gate errors caused by SEUs. In this paper, we compare the probabilities of single and multiple errors. We formulate a criterion based on gate error probabilities for considering multiple gate errors in circuit reliability. Gate error probabilities are increased by technology trends such as the down-scaling of device ...

Abstract—Approximations to the union bound performance of sequence detection in the presence of colored noise and an algorithm to compute bit error and error event probabilities are presented and compared to bitby-bit simulation results. These computations, which are very accurate at bit error probabilities , are then used to analyze the performance of standard and reverse concatenated Reed-Sol...

Feed forward neural networks are compared with standard and new statistical classification procedures for the classification of proteins. We applied logistic regression, an additive model and projection pursuit regression from the methods based on a posterior probabilities; linear, quadratic and a flexible discriminant analysis from the methods based on class conditional probabilities, and the ...

–Obtain a sampling resolution comparable to 6 responses per stimulus (580 responses) in a time of 30 minutes. Procedure 1. All stimuli are presented twice in random order, the listener identifies the stimuli (180 responses). 2. A logistic regression model is fitted to the response data, and the predicted probabilities of each category for each stimulus are calculated. 3. The error between the o...

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In this paper, we introduce a new concept, the time frame error rate. We show that this error rate is closely correlated with the word error rate and use it to overcome the mismatch between Bayes’ decision rule which aims at minimizing the expected sentence error rate and the word error rate which is used to assess the performance of speech recognition systems. Based on the time frame errors we...

Current approaches for the prediction of functional relations from gene expression data often do not have a clear methodology for extracting features and are not accompanied by a clear characterisation of their performance in terms of the inherent noise present in such data sets. Without such a characterisation it is unclear how to focus on the most probable functional relations present. In thi...

Precise analytical asymptotic exponential rates of error, and bounds on those rates, for diierential multiple-phase-shift keying (DMPSK) systems that include post-detection integration are provided. Easily computed bounds on these rates are provided, both in the case of oor bit error probability (i.e., with no additive noise) and in the case of weak additive noise. The derivation uses the theor...

We derive Chernoff bounds on pairwise error probabilities of coherent and noncoherent space-time signaling schemes. First, general Chernoff bound expressions are derived for a correlated Ricean fading channel and correlated additive Gaussian noise. Then, we specialize the obtained results to the cases of space-timeseparable noise, white noise, and uncorrelated fading. We derive approximate Cher...