نتایج جستجو برای: principle component analysis (pca)

تعداد نتایج: 3382418  

ژورنال: :تولیدات گیاهی 0
امیر مرادی سراب شلی دانشجوی کارشناسی ارشد گروه زراعت و اصلاح نباتات، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران محمدرضا نقوی استاد گروه زراعت و اصلاح نباتات، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران محمدجعفر آقایی استادیار موسسه اصلاح و تهیه نهال و بذر کرج، بخش غلات

to evaluate the genetic diversity, four wild wheat species named t. boeticum, t. thaudar, t. urartu, t. arrarticum were studied. quantitative traits were measured according to ibpgri. analysis of variance showed significant difference for all landraces. result of pearson correlation analysis showed positive and negative significant correlations between some of the traits. in principle component...

Journal: :TELKOMNIKA (Telecommunication Computing Electronics and Control) 2007

Journal: :journal of industrial engineering, international 2011
alimohammad ahmadvand zeinab abtahy mahdi bashiri

this paper presents a deterministic approach for performance assessment of different province’s road safety level at iran. a data envelopment analysis (dea) model considering undesirable input and output indices and a multivariate statistical method, principle component analysis (pca) are used in this paper, while previous studies do not use composite pca-dea method and undesirable input and ou...

2013
Paul Augustine Tripti

Development in Human Computer Interactions (HCI) helps in budding user friendly systems to communicate with computers. One of the fundamental techniques that aid Human Computer Interaction (HCI) is face recognition. Face recognition is one of the most successful applications of image analysis and pattern recognition. Principle Component Analysis (PCA) is considered as the first real time face r...

Journal: :journal of biomedical physics and engineering 0
a karimi rahmati control and intelligent processing center of excellence, school of electrical and computer engineering, college of engin s k setarehdan control and intelligent processing center of excellence, school of electrical and computer engineering, college of enginسازمان اصلی تایید شده: دانشگاه تهران (tehran university) b n araabi control and intelligent processing center of excellence, school of electrical and computer engineering, college of enginسازمان اصلی تایید شده: دانشگاه تهران (tehran university)

background: fetal electrocardiography is a developing field that provides valuable information on the fetal health during pregnancy. by early diagnosis and treatment of fetal heart problems, more survival chance is given to the infant. objective: here, we extract fetal ecg from maternal abdominal recordings and detect r-peaks in order to recognize fetal heart rate. on the next step, we find a b...

Journal: :international journal of advanced biological and biomedical research 0
nazlar ghassemzadeh ms student, department of biomedical engineering, tabriz branch , islamic azad university tabriz , iran siamak haghipour assistant professor, department of biomedical engineering, tabriz branch, islamic azad university tabriz, iran

the brain – computer interface (bci) provides a communicational channel between human and machine. most of these systems are based on brain activities. brain computer-interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. the success of this methodology depends on the selection of methods to process the brain signals in each pha...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه شیراز - دانشکده علوم 1388

این تحقیق با استفاده آنالیز چند متغیره بر روی عکس های ذخیره شده بوسیله یک دوربین دیجیتال راه حلی را برای مسئله همپوشانی پیک ها که یکی از مسائل مهم در کروماتوگرافی لایه نازک است ارائه میدهد. ما برای اولین بار اندازه گیری همزمان چند گونه بر روی کاغذ کروماتوگرافی لایه نازک را با استفاده از آنالیز چند متغیره عکس مورد مطالعه قرار دادیم. سیستم عکسبرداری متشکل از یک کابینت، یک دوربین دیجیتال و یک بر...

Journal: :CoRR 2011
Soumen Bag Soumen Barik Prithwiraj Sen Gautam Sanyal

Keywords: Eigenface, face Recognition, k-means clustering, principle component analysis (PCA)

2005
Duy-Dinh Le Shin'ichi Satoh

We propose a simple yet efficient feature-selection method — based on principle component analysis (PCA) — for SVM-based classifiers. The idea is to select features whose corresponding axes are closest to the principle components computed from a data distribution by PCA. Experimental results show that our proposed method reduces dimensionality similar to PCA, but maintains the original measurem...

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