نتایج جستجو برای: expectation maximization em algorithm has been used for modeling extreme value based on peak over threshold approach
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abstract venlafaxine, 1–[2–(dimethylamino)–1–(4–methoxyphenyl) ethyl]cyclohexanol hydrochloride is a novel non-tricyclic antidepressant. venlafaxine is a second generation antidepressant drug, has a neuropharmacologic profile distinct from that of existing antidepressants including tricyclic compounds, selective serotonin reuptake inhibitors and monoamine oxidase inhibitors. venlafaxine impart...
introduction: diabetes mellitus is an growing national and international public health concern. the number of people affected by diabetes in world by 2030 will be 69% in developing countries. regular physical activity plays a key role in the management of type 2 diabetes melitus, particularly glycemic control. it has been recommended that peoples with type 2 diabetes participate in moderate-int...
Maximum likelihood estimation (MLE) is one of the most important methods in machine learning, and the expectation-maximization (EM) algorithm is often used to obtain maximum likelihood estimates. However, EM heavily depends on initial configurations and fails to find the global optimum. On the other hand, in the field of physics, quantum annealing (QA) was proposed as a novel optimization appro...
Factor analysis is a statistical covariance modeling technique based on the assumption of normally distributed data. A mixture of factor analyzers can be hence viewed as a special case of Gaussian (normal) mixture models providing a mathematically sound framework for attribute space dimensionality reduction. A significant shortcoming of mixtures of factor analyzers is the vulnerability of norma...
abstract the present study tried to investigate the effect of visual aids (films) on the development of the speech act of disagreement among iranian efl intermediate learners. to this end, the researcher selected 40 homogeneous intermediate learners based on their scores on oxford placement test. .the subjects then divided into control group and experimental group. both classes were tested by ...
Image segmentation is to partition an image into meaningful regions with respect to a particular application. Object recognition is the task of finding a given object in an image or video sequence. This paper discusses the interaction between image segmentation and object recognition in the framework of the Expectation-Maximization (EM) algorithm. Threshold is image processing technique for con...
assigning premium to the insurance contract in iran mostly has based on some old rules have been authorized by government, in such a situation predicting premium by analyzing database and it’s characteristics will be definitely such a big mistake. therefore the most beneficial information one can gathered from these data is the amount of loss happens during one contract to predicting insurance ...
the purpose of this study was to investigate the relationship between family functioning and marital adjustment humor couples are due to the nature and objectives of the research and application of methods for its implementation correlation was used. the study population consisted of all the couples in the city who uses random cluster sampling of 200 students were selected as sample. data from ...
deposite the different criticisms on contrastive analysis it has been proved that the results of it(when processed)can be usuful in a tefl environment,specially at the level of phonology.this study is an attempt to compare and contrast the sound systems of kurdish and english for pedagogical aims. the consonants,vowels,stress and intonation of the twolanguages are described by the same model-ta...
We present the Trusted Expectation-Maximization (TEM), a new discriminative training scheme, for speech recognition applications. In particular, the TEM algorithm may be used for Hidden Markov Models (HMMs) based discriminative training. The TEM algorithm has a form similar to the ExpectationMaximization (EM) algorithm, which is an efficient iterative procedure to perform maximum likelihood in ...
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