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Search results for: MATCHING PURSUIT
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Identification of Non-Stationary Magnetic Field Sources Using the Matching Pursuit Method
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Application of matching pursuit based method to identify sources of time-vary magnetic field
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White Clover (Trifolium repens L.) Cultivation as a Means of Soil Regeneration and Pursuit of a Sustainable Food System Model
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Journal of Machine Construction and Maintenance
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Pursuing Analytically the Influence of Hearing Aid Use on Auditory Perception in Various Acoustic Situations
PublicationThe paper presents the development of a method for assessing auditory perception and the effectiveness of applying hearing aids for hard-of-hearing people during short-term (up to 7 days) and longer-term (up to 3 months) use. The method consists of a survey based on the APHAB questionnaire. Additional criteria such as the degree of hearing loss, technological level of hearing aids used, as well as the user experience are taken...
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MACHINE DYNAMICS PROBLEMS
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Machine Translation
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MACHINE LEARNING
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