The Labeled Magnitude Scale (LMS) is a semantic scale of perceptual intensity characterized by a quasi-logarithmic spacing of its verbal labels. The LMS had previously been shown to yield psychophysical functions equivalent to magnitude estimation (ME) when gustatory, thermal and nociceptive stimuli were presented and rated together, and the upper bound of the LMS was defined as the 'strongest ...

In this paper we discuss how to improve the behavior of the Variable Step-Size LMS (VSSLMS) algorithm that was proposed in [6]. In many practical applications from the field of system identification, an estimation of the noise variance is available. Therefore we introduce a modified VS-LMS algorithm that exploits this informations in order to provide a faster convergence speed. In this paper th...

In this work, a new class of stochastic gradient algorithm is developed based on q-calculus. Unlike the existing q-LMS algorithm, the proposed approach fully utilizes the concept of q-calculus by incorporating time-varying q parameter. The proposed enhanced q-LMS (Eq-LMS) algorithm utilizes a novel, parameterless concept of error-correlation energy and normalization of signal to ensure high con...

This paper introduces a cascade d RLS-LMS predictor for predictive lossless audio coding applications. In this proposed predictor, a LMS predictor with large order is employed in order to capture the ample tonal and harmonic components of the audio signal for optimal prediction gain performance. Meanwhile, to solve the slow convergence problem of the LMS algorithm with colored inputs, a low-ord...

The stochastic-gradient-descent LMS adaptive filtering algorithm provides a powerful and computationally efficient means of realizing adaptive filters. In this work, we present architectural synthesis of low-power computational engines (or hardware accelerators) for LMS adaptive filtering. This engine could be configured for delayed LMS/delayed normalized LMS, full-band/subband adaptive filteri...

The aim of this paper is to implement various adaptive noise cancellers (ANC) for speech enhancement based on gradient descent approach, namely the least-mean square (LMS) algorithm and then enhanced to variable step size strategy. In practical application of the LMS algorithm, a key parameter is the step size. As is well known, if the step size is large, the convergence rate of the LMS algorit...

OBJECTIVE Primary objective of this study was to evaluate the impact of significant left main stem (LMS) stenosis on the early outcome of coronary artery bypass graft (CABG) surgery. METHODS A Retrospective non-randomized analytical study was conducted in Cardiac surgery department, Chaudhary Pervaiz Elahi Institute of Cardiology (CPEIC) Multan, Pakistan. The data of patients who underwent is...

OBJECTIVE Enzymatic metabolism of polyunsaturated fatty acids leads to formation of bioactive lipid metabolites (LMs). Previous studies have shown that obesity leads to deregulation of LMs in adipose tissues. However, most previous studies have focused on a single or limited number of LMs, and few systematical analyses have been carried out. METHODS A LC-MS/MS-based lipidomics approach was us...

Recently, freestanding lms have attracted much attention because they are highly useful in the fabrication of various nanodevices. Freestanding lms can be used on any substrate without deterioration of their own unique properties. Layerby-layer (LBL) deposition has been used widely in the synthesis of freestanding lms, especially of polymer lms with specic physical and mechanical propertie...

The paper proposes a new adaptive VS LMS algorithm, obtained by combining LMS algorithms with different step sizes without calculating their weighting coefficients. As a criterion for choosing the VS LMS algorithm step size, we take the ratio between the weighting coefficients' bias and variance. Identification of an unknown system in nonstationary noisy environment is performed and simulations...