Least median of squares (LMS) regression is a robust method to t equations to observed data (typically in a linear model). This paper describes an approximation algorithm for LMS regression. The algorithm generates a regression solution with median residual no more than twice the optimal median residual. Random sampling is used to provide a simple O(n log 2 n) expected time algorithm in the two...

ECG signals have been proven a very versatile tool for detection of cardiovascular diseases. But during recording of these signals, the ECG data gets contaminated by various noise signals caused by power line interference, base line wander, electrode movement, muscle movement (EMG) etc. These noise signals are known as artifacts. These artifacts mislead the diagnosis of heart which is not desir...

In this paper we present a pruning algorithm and experimental results for our recently proposed Sparse Non-negative Matrix (SNM) family of language models (LMs). We show that when trained with only n-gram features SNMLM pruning based on a mutual information criterion yields the best known pruned model on the One Billion Word Language Model Benchmark, reducing perplexity with 18% and 57% over Ka...

We establish the consistency, asymptotic normality, and efficiency for estimators derived by minimizing the median of a loss function in a Bayesian context. We contrast this procedure with the behavior of two Frequentist procedures, the least median of squares (LMS) and the least trimmed squares (LTS) estimators, in regression problems. The LMS estimator is the Frequentist version of our estima...

In this contribution a new technique for adjusting the stepsize of the LMS algorithm is introduced. The proposed method adjusts the step-size sequence utilising the kurtosis of the estimation error, reducing therefore performance degradation due to the existence of significant gaussiandistributed noise. The algorithm’s behaviour is analysed and equations regarding the evolution of the weight-er...

We analyze subword-based language models (LMs) in large-vocabulary continuous speech recognition across four “morphologically rich” languages: Finnish, Estonian, Turkish, and Egyptian Colloquial Arabic. By estimating n-gram LMs over sequences of morphs instead of words, better vocabulary coverage and reduced data sparsity is obtained. Standard word LMs suffer from high out-of-vocabulary (OOV) r...

Leiomyosarcoma (LMS) is a rare malignant mesenchymal tumor of smooth muscle cells. Chromosomal aberrations in LMS have been studied, but the cytogenetic data that have been published so far are complex, limited, and incomplete. Here, we performed for the first time a high-resolution genome-wide array comparative genomic hybridization (CGH) analysis (aCGH) on a pool of 14 low- and high-grade LMS...

<p style="text-align: justify;">The learning management system (LMS) is a crucial component of the e-learning transformation which becoming more urgent amid Coronavirus disease (COVID-19) outbreak. The issue adopting LMS even decisive in developing countries, where lots efforts have been put out to broaden educational opportunities. However, there has not yet any comprehensive analysis ho...

This paper presents a distinctive phonetic features (DPFs) based phoneme recognition method by incorporating syllable language models (LMs). The method comprises three stages. The first stage extracts three DPF vectors of 15 dimensions each from local features (LFs) of an input speech signal using three multilayer neural networks (MLNs). The second stage incorporates an Inhibition/Enhancement (...