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排序方式: 共有789条查询结果,搜索用时 9 毫秒
1.
Abbass Mohammed Y. Kwon Ki-Chul Kim Nam Abdelwahab Safey A. El-Samie Fathi E. Abd Khalaf Ashraf A. M. 《Artificial Intelligence Review》2021,54(5):3349-3360
Artificial Intelligence Review - Visual object tracking has become one of the most active research topics in computer vision, and it has been applied in several commercial... 相似文献
2.
Rasoul Rahmani Nima M. A. Langeroudi Rozbeh Yousefi Milad Mahdian Mohammadmehdi Seyedmahmoudian 《Neural computing & applications》2014,25(3-4):879-888
In this paper, a five-level cascaded H-bridge multilevel inverters topology is applied on induction motor control known as direct torque control (DTC) strategy. More inverter states can be generated by a five-level inverter which improves voltage selection capability. This paper also introduces two different control methods to select the appropriate output voltage vector for reducing the torque and flux error to zero. The first is based on the conventional DTC scheme using a pair of hysteresis comparators and look up table to select the output voltage vector for controlling the torque and flux. The second is based on a new fuzzy logic controller using Sugeno as the inference method to select the output voltage vector by replacing the hysteresis comparators and lookup table in the conventional DTC, to which the results show more reduction in torque ripple and feasibility of smooth stator current. By using Matlab/Simulink, it is verified that using five-level inverter in DTC drive can reduce the torque ripple in comparison with conventional DTC, and further torque ripple reduction is obtained by applying fuzzy logic controller. The simulation results have also verified that using a fuzzy controller instead of a hysteresis controller has resulted in reduction in the flux ripples significantly as well as reduces the total harmonic distortion of the stator current to below 4 %. 相似文献
3.
The phospholipid fatty acid composition of the Calcarean spongeLeucosolenia canariensis was studied, and no Δ5,9 fatty acids were detected. These results are in contrast to the phospholipids from sponges belonging to the class Demospongiae
where Δ5,9 fatty acids are predominant. Odd branched-chain fatty acids between 17 and 19 carbons accounted for 26% of the
total fatty acids ofL. canariensis, while straight-chain fatty acids between 16 and 22 carbons accounted for 61% of the total fatty acid composition. The sterol
composition ofL. canariensis is also reported, and only Δ5,7,22 sterols were observed. 相似文献
4.
Marwa A. Abd El-Fattah Moawad I. Dessouky Alaa M. Abbas Salaheldin M. Diab El-Sayed M. El-Rabaie Waleed Al-Nuaimy Saleh A. Alshebeili Fathi E. Abd El-samie 《International Journal of Speech Technology》2014,17(1):53-64
This paper proposes an adaptive Wiener filtering method for speech enhancement. This method depends on the adaptation of the filter transfer function from sample to sample based on the speech signal statistics; the local mean and the local variance. It is implemented in the time domain rather than in the frequency domain to accommodate for the time-varying nature of the speech signals. The proposed method is compared to the traditional frequency-domain Wiener filtering, spectral subtraction and wavelet denoising methods using different speech quality metrics. The simulation results reveal the superiority of the proposed Wiener filtering method in the case of Additive White Gaussian Noise (AWGN) as well as colored noise. 相似文献
5.
Majid Alizadeh Moghadam Reza Mohammadi Ehsan Sadeghi Mohammad Amin Mohammadifar Mohammad Nejatian Maryam Fallah Milad Rouhi 《应用聚合物科学杂志》2021,138(28):50672
The effects of gum tragacanth obtained from two species of Astragalus Gossypinus (GT-G) and A. Parrowianus (GT-P) at two levels of 10% and 30% combined with cellulose nanofibers (CNF; 5%) on the physico-mechanical and structural properties of polyvinyl alcohol (PVA) nanocomposite film were investigated in this study. The water solubility and water vapor permeability of the films decreased with increasing the content of both gums, especially in the film containing 30% GT-P. The highest values of the tensile strength (39.3 MPa) and elongation at break (445%) belonged to the treatment containing 10% GT-P (90/10P/0). The FTIR and DSC analyses confirmed good interactions between GT and PVA in the 90/10P/0 treatment. SEM images indicated the dense structure of this film as the optimum treatment. Although the presence of CNF in the films containing GT-G improved some properties, especially the Young modulus, it impaired all the functional properties of nanocomposite GT-P film. 相似文献
6.
7.
Fathi E. Abd El-Samie 《International Journal of Speech Technology》2009,12(1):27-45
The singular value decomposition (SVD) mathematical technique is utilized, in this paper, for audio watermarking in time and
transform domains. Firstly, the audio signal in time or an appropriate transform domain is transformed to a 2-D format. The
SVD algorithm is applied on this 2-D matrix, and an image watermark is added to the matrix of singular values (SVs) with a
small weight, to guarantee the possible extraction of the watermark without introducing harmful distortions to the audio signal.
The transformation of the audio signal between the 1-D and 2-D formats is performed in the well-known lexicographic ordering
method used in image processing. A comparison study is presented in the paper between the time and transform domains as possible
hosting media for watermark embedding. Experimental results are in favor of watermark embedding in the time domain if the
distortion level in the audio signal is to be kept as low as possible with a high detection probability. The proposed algorithm
is utilized also for embedding chaotic encrypted watermarks to increase the level of security. Experimental results show that
watermarks embedded with the proposed algorithm can survive several attacks. A segment-by-segment implementation of the proposed
SVD audio watermarking algorithm is also presented to enhance the detectability of the watermark in the presence of severe
attacks. 相似文献
8.
9.
Applying Dynamic Training‐Subset Selection Methods Using Genetic Programming for Forecasting Implied Volatility
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Volatility is a key variable in option pricing, trading, and hedging strategies. The purpose of this article is to improve the accuracy of forecasting implied volatility using an extension of genetic programming (GP) by means of dynamic training‐subset selection methods. These methods manipulate the training data in order to improve the out‐of‐sample patterns fitting. When applied with the static subset selection method using a single training data sample, GP could generate forecasting models, which are not adapted to some out‐of‐sample fitness cases. In order to improve the predictive accuracy of generated GP patterns, dynamic subset selection methods are introduced to the GP algorithm allowing a regular change of the training sample during evolution. Four dynamic training‐subset selection methods are proposed based on random, sequential, or adaptive subset selection. The latest approach uses an adaptive subset weight measuring the sample difficulty according to the fitness cases' errors. Using real data from S&P500 index options, these techniques are compared with the static subset selection method. Based on mean squared error total and percentage of non‐fitted observations, results show that the dynamic approach improves the forecasting performance of the generated GP models, especially those obtained from the adaptive‐random training‐subset selection method applied to the whole set of training samples. 相似文献
10.
Probability of withdrawal is a feature of initial public offering (IPOs), which can be an important parameter in decisions of investors and issuers. Considering the probability of offering withdrawal facilitates more precise estimation of underpricing. In this paper, the effective factors on probability of IPO withdrawal and underpricing in Tehran Stock Exchange have been characterized using regression, and then neural network is applied to estimate the probability of IPO withdrawal and underpricing. To evaluate the performance of our applied method, fuzzy regression is employed and compared with neural network. According to the obtained empirical results, neural network demonstrates better accuracy than fuzzy regression. The results indicate that there is a meaningful relationship between underpricing and probability of withdrawal, and the probability of IPO withdrawal plays an important role in precise evaluation of underpricing. 相似文献