نتایج جستجو برای: طبقهبندی کنندهای LDA و LS-SVM
تعداد نتایج: 797295 فیلتر نتایج به سال:
طبقه بندی حرکت های اعضای دیستال با استفاده از سیگنال های الکترومایوگرام سطحیِ (semg) قسمت پروکسیمال، بخش مهمی در کنترل پروتزهای مایوالکتریک است. در بیشتر مطالعات قبلی، طبقه بندیِ تعداد محدودی از حرکت های دست مورد بررسی قرار گرفته است. در این مقاله، از پایگاه داده ی ninapro که شامل داده های کینماتیک و semg فرد سالم برای 52 حرکت انگشت، پنجه و مچ دست است استفاده کرده ایم. در این مطالعه، عملکرد طبقه ...
This study investigated the feasibility of using near infrared hyperspectral imaging (NIR-HSI) technique for non-destructive identification of sesame oil. Hyperspectral images of four varieties of sesame oil were obtained in the spectral region of 874-1734 nm. Reflectance values were extracted from each region of interest (ROI) of each sample. Competitive adaptive reweighted sampling (CARS), su...
طبقه بندی حرکت های اعضای دیستال با استفاده از سیگنال های الکترومایوگرام سطحیِ (semg) قسمت پروکسیمال، بخش مهمی در کنترل پروتزهای مایوالکتریک است. در بیشتر مطالعات قبلی، طبقه بندیِ تعداد محدودی از حرکت های دست مورد بررسی قرار گرفته است. در این مقاله، از پایگاه داده ی ninapro که شامل داده های کینماتیک و semg فرد سالم برای 52 حرکت انگشت، پنجه و مچ دست است استفاده کرده ایم. در این مطالعه، عملکرد طبقه ...
Ability to predict direction of stock/index price accurately is crucial for market dealers or investors to maximize their profits. Data mining techniques have been successfully shown to generate high forecasting accuracy of stock price movement. Nowadays, in stead of a single method, traders need to use various forecasting techniques to gain multiple signals and more information about the futur...
There has been a growing research interest in brain tumor classification based on proton magnetic resonance spectroscopy (1H MRS) signals. Four research centers within the EU funded INTERPRET project have acquired a significant number of long echo 1H MRS signals for brain tumor classification. In this paper, we present an objective comparison of several classification techniques applied to the ...
a quantitative structure–activity relationship (qsar) study is suggested for the prediction of biological activity (pic 50 ) of 3, 4-dihydropyrido [3 ,2-d] pyrimidone derivatives as p38 inhibitors. modeling of the biological activities of compounds of interest as a function of molecular structures was established by means of principal component analysis (pca) and least square support vector mac...
The success of myoelectric pattern recognition (M-PR) mostly relies on the features extracted and classifier employed. This paper proposes and evaluates a fast classifier, extreme learning machine (ELM), to classify individual and combined finger movements on amputees and non-amputees. ELM is a single hidden layer feed-forward network (SLFN) that avoids iterative learning by determining input w...
Bruise may cause spoilage, reduce commodity economic value, and give rise to food quality safety concerns. Therefore, it is crucial detect whether a loquat bruised when save storage transportation costs. At present, the bruise of loquats mainly discriminated by operator’s naked eye, which affected personal habits, light intensity, subjective psychological factors. The detection method time-cons...
a method based on electrical capacitance tomography (ect) and an improved least squares support vector machine (ls-svm) is proposed for void fraction measurement of oil-gas two-phase flow. in the modeling stage, to solve the two problems in ls-svm, pruning skills are employed to make ls-svm sparse and robust; then the real-coded genetic algorithm is introduced to solve the difficult problem of ...
Linear discriminant analysis (LDA) is a popular dimensionality reduction and classification method that simultaneously maximizes between-class scatter and minimizes within-class scatter. In this paper, we verify the equivalence of LDA and least squares (LS) with a set of dependent variable matrices. The equivalence is in the sense that the LDA solution matrix and the LS solution matrix have the...
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