نتایج جستجو برای: performance vector

تعداد نتایج: 1218862  

In this paper, we present a Compressive Sampling (CS)-based feature extraction method for audio signals. In the proposed approach, the audio signal is firstly segmented by hamming windows and the Discrete Fourier Transform (DFT) of the samples is calculated within each frame. Then, the normalized values of the DFT coefficients of each frame are accumulated. At the next step, the second DFT is a...

Abstract In this work, a support vector machine (SVM) model was developed to predict the hot deformation flow curves of AZ91 magnesium alloy. The experimental stress-strain curves, obtained from hot compression testing at different deformation conditions, were sampled. Consequently, a data base with the input variables of the deformation temperature, strain rate and strain and the output variab...

in this paper we focus on the tracking performance of incremental adaptive LMS algorithm in an adaptive network. For this reason we consider the unknown weight vector to be a time varying sequence. First we analyze the performance of network in tracking a time varying weight vector and then we explain the estimation of Rayleigh fading channel through a random walk model. Closed form relations a...

Fault diagnosis has always been an essential aspect of control system design. This is necessary due to the growing demand for increased performance and safety of industrial systems is discussed. Support vector machine classifier is a new technique based on statistical learning theory and is designed to reduce structural bias. Support vector machine classification in many applications in v...

پایان نامه :دانشگاه تربیت معلم - تهران - دانشکده ادبیات و علوم انسانی 1390

abstract the variables affecting the nature of reading comprehension can be classified into two general categories: reader’s variables, and text variables (alderson, 2000). despite the wave of research on vocabulary knowledge as reader’s variable, the role of this knowledge in c-test as a text-dependent test and its interaction with lexical cohesion of the test as a text feature has remained a...

Abdolhamid Sameni, Ali Chamkalani

The problem of slow drilling in deep shale formations occurs worldwide causing significant expenses to the oil industry. Bit balling which is widely considered as the main cause of poor bit performance in shales, especially deep shales, is being drilled with water-based mud. Therefore, efforts have been made to develop a model to diagnose drilling effectivity. Hence, we arrived at graphical cor...

2008
Jonathan Paul Kitchens Arthur B. Baggeroer

Classical hydrophones measure pressure only, but acoustic vector-sensors also measure particle velocity. Velocity measurements can increase array gain and resolve ambiguities, but make vector-sensor arrays more difficult to analyze. This thesis derives a new set of useful performance measures for acoustic vector-sensor arrays. It characterizes the vector-sensor array beampattern with and withou...

In recent years, some researches have been done on simultaneous monitoring of multivariate process mean vector and covariance matrix. However, the effect of measurement error, which exists in many practical applications, on the performance of these control charts is not well studied. In this paper, the effect of measurement error with linearly increasing variance on the performance of ELR contr...

2014
Sargur N. Srihari Gang Chen Zhen Xu Lisa Hanson

The individuality of handwriting is the principal underpinning of forensic handwriting examination. Studies of individuality have considered different statistical extremes to obtain handwriting samples. The first is a representative population drawn from a country. The second is a population of twins– so as to reflect genetic similarity. A third approach is to study whether teachers and schools...

2007
Haibin Cheng Haifeng Chen Guofei Jiang Kenji Yoshihira

Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between features. However it is known that the number of support vectors required in SVM typically grows linearly with the size of the training data set. Such a limitation of SVM becomes more critical when we need to select a sma...

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