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Search results for: Statistical time series methods
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Using Statistical Methods to Estimate The Worst Case Response Time of Network Software Running on Indeterministic Hardware Platforms
PublicationIn this paper we investigate whether the statistical Worst Case Execution Time (WCET) estimation methods devised for embedded platforms can be successfully applied to find the Worst Case Response Time (WCRT) of a network application running on a complex hardware platform such as a contemporary commercial off-the-shelf (COTS) system. Establishing easy-to-use timing validation techniques is crucial for real-time applications and...
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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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Investigation of noises in the EPN weekly time series
PublicationThe constantly growing needs of permanent stati ons’ velocities users cause their stability level to increase. To this research we included more than 150 stations located across Europe operating within the EUREF Permanent Network (EPN) w ith weekly changes in the ITRF2005 reference frame. The obvious long-range dependencies in the stochastic part of GPS time series were p roven by Ljung-Box...
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TIME SERIES DATA FOR 3D FLOOD MAPPING
PublicationThanks to the ability to collect information about large areas and with high frequency in time areas threatened by floods can be closely monitored. The effects of flooding are socio-economic losses. In order to reduce those losses, actions related to the determination of building zones are taken. Moreover, the conditions to be met by facilities approved for implementation in such areas are determined. Therefore, satellite data...
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Time series - the tool for traffic safety analysis
PublicationGłównym celem artykułu jest przedstawienie sposobu modelowania i modeli stosowanych w analizach i prognozowaniu odnośnie zmian śmiertelności w wypadkach drogowych w Polsce. W tym celu zastosowano teorię modeli strukturalnych szeregów czasowych przy założeniu, że zarówno ruch drogowy, jak i bezpieczeństwo na drogach są procesami dynamicznymi, w których przeszłość ma znaczący wpływ na teraźniejszość i przyszłość systemu.
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Short-Period Information in GPS Time Series
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Traffic fatalities modelling using time-series.
PublicationReferat zawiera opis jednaj z metod analizowania trendów bezpieczeństwa ruchu drogowego opartej na teorii szeregów czasowych. Przedstawiono w nim aplikację tej metody do badania związku pomiędzy liczbą śmiertelnych ofiar wypadków drogowych w Polsce w latach 1991-2003 a wielkością bezrobocia w tym czasie.
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Traffic risk modelling using time-series
PublicationW referacie przedstawiono metodę prognozowania ryzyka w ruchu drogowym powstałą na bazie analizy szeregów czasowych. W jej oparciu dla danych o liczbie śmiertelnych ofiar wypadków drogowych w Polsce w latach 1989-2000 zbudowano model i wykonano prognozę rozwoju trendu w przyszłości.
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A new multi-process collaborative architecture for time series classification
PublicationTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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Entropy of Financial Time Series Due to the Shock of War
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On the Handling of Outliers in the GNSS Time Series by Means of the Noise and Probability Analysis
PublicationThe data pre-analysis plays a significant role in the noise determination. The most important issue is to find an optimum criterion for outliers removal, since their existence can affect any further analysis. The noises in the GNSS time series are characterized by spectral index and amplitudes that can be determined with a few different methods. In this research, the Maximum Likelihood Estimation (MLE) was used. The noise amplitudes...
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Statistical Method for Analysis of Interactions Between Chosen Protein and Chondroitin Sulfate in an Aqueous Environment
PublicationWe present the statistical method to study the interaction between a chosen protein and another molecule (e.g., both being components of lubricin found in synovial fluid) in a water environment. The research is performed on the example of univariate time series of chosen features of the dynamics of mucin, which interact with chondroitin sulfate (4 and 6) in four different saline solutions. Our statistical approach is based on recurrence...
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Road safety analysis in Poland using time-series modelling techniques
PublicationA number of international studies argue that there is a correlation between the number of traffic fatalities and the degree of public activity. The studies use the unemployment rate to support that argument. As unemployment grows miles travelled fall, a factor known to affect road safety. This relationship seems to be true for Poland, as well. The model presented in the paper is intended to prove it. It is a structural time-series local...
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Irregular variations in GPS time series by probability and noise analysis
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Application of PCA and time series analysis in studies of precipitation in Tricity (Poland).
PublicationPrzedstawiono wyniki monitoringu zanieczyszczenia atmosfery Trójmiasta. Próbki wody opadowej pobierano w cyklach miesięcznych przez 4 lata (1998-2001)w 10 punktach. Wyniki poddano statystycznej i chemometrycznej analizie (szeregi czasowe, analiza wariancji, analiza głównych składowych). Wykazano wpływ lokalizacji punktów monitoringowych i bliskości Morza Bałtyckiego na zawartość jonów nieorganicznych w analizowanych próbkach.
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Ontological Model for Contextual Data Defining Time Series for Emotion Recognition and Analysis
PublicationOne of the major challenges facing the field of Affective Computing is the reusability of datasets. Existing affective-related datasets are not consistent with each other, they store a variety of information in different forms, different formats, and the terms used to describe them are not unified. This paper proposes a new ontology, ROAD, as a solution to this problem, by formally describing the datasets and unifying the terms...
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Safety Assessment of the Regional Warmia and Mazury Road Network Using Time-Series Analysis
PublicationWarmia and Mazury still belongs to the areas with the smallest transport accessibility in Europe. Unsatisfactory state of road infrastructure is a major barrier to the development of the regional economy, impacting negatively on the life conditions of the population. Also in terms of road safety Warmia and Mazury is one of the most endangered regions in Poland. The Police statistics show that beside a high pedestrian risk observed...
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Autocovariance based weighting strategy for time series prediction with weighted LS-SVM
PublicationPrzedstawiono metodę konstrukcji algorytmów z funkcją jądra, a także dwa algorytmy uzyskane poprzez użycie różnych funkcji straty. Zaproponowano kowariacyjną strategię ważenia algorytmów z kwadratową funkcją straty do problemu predykcji chaotycznych przebiegów czasowych.
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Application of time-series-cross-section data in case of sale forecasting in an enterprise
PublicationW artykule wskazano możliwości wykorzystania danych przestrzenno-czasowych do prognozowania sprzedaży w przedsiębiorstwie. Przedstawiono różne podejścia do prognozowania ekonometrycznego przy użyciu tego typu danych. Wyznaczono krótkookresowe prognozy sprzedaży benzyny bezołowiowej Pb95 w przekroju województw oraz dokonano oceny ich jakości przy użyciu mierników ex-post. Dwie najdokładniejsze metody prognozowania wykorzystano do...
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Price bubbles in commodity market – A single time series and panel data analysis
PublicationThis paper examines thirty-five commodities, grouped into three market sectors (energy, metals, agriculture & livestock) in terms of the occurrence of price bubbles. The study was based on monthly data for each commodity separately and, in a panel approach, for selected sectors and for all commodities combined. The GSADF test and its version for panel data – panel GSADF – were used to identify bubbles. The beginning and end of...
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Time-series analysis of road safety trends aggregated at national level in Europe for 2000-2010
PublicationThe reader will find in this study road safety modelling theory and time-series analysis techniques, applications to long period data of injury accidents and casualities, aggregared at national level
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Flooding Extent Mapping for Synthetic Aperture Radar Time Series Using River Gauge Observations
PublicationThe flooding extent area in a river valley is related to river gauge observations such as discharge and water elevations. The higher the water elevations, or discharge, the larger the flooding area. Flooding extent maps are often derived from synthetic aperture radar (SAR) images using thresholding methods. The thresholding methods vary in complexity and number of required parameters. We proposed a simple thresholding method that...
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Excited state properties of a series of molecular photocatalysts investigated by time dependent density functional theory.
PublicationTime dependent density functional theory calculations are applied on a series of molecular photocatalysts of the type [(tbbpy)2M1(tpphz)M2X2]2+ (M1 = Ru, Os; M2 = Pd, Pt; X = Cl, I) in order to provide information concerning the photochemistry occurring upon excitation of the compounds in the visible region. To this aim, the energies, oscillator strengths and orbital characters of the singlet and triplet excited states are investigated....
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Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS Data Processing
PublicationThe GPS system can play an important role in activities related to the monitoring of climate. Long time series, coherent strategy, and very high quality of tropospheric parameter Zenith Tropospheric Delay (ZTD) estimated on the basis of GPS data analysis allows to investigate its usefulness for climate research as a direct GPS product. This paper presents results of analysis of 16-year time series derived from EUREF Permanent Network...
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Testing heart rate asymmetry in long, nonstationary 24 hour RR-interval time series
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Assessment of the Impact of GNSS Processing Strategies on the Long-Term Parameters of 20 Years IWV Time Series
PublicationAdvanced processing of collected global navigation satellite systems (GNSS) observations allows for the estimation of zenith tropospheric delay (ZTD), which in turn can be converted to the integrated water vapour (IWV). The proper estimation of GNSS IWV can be affected by the adopted GNSS processing strategy. To verify which of its elements cause deterioration and which improve the estimated GNSS IWV, we conducted eight reprocessings...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Road Safety Trends at National Level in Europe: A Review of Time-series Analysis Performed during the Period 2000–12
PublicationThis paper presents a review of time-series analysis of road safety trends, aggregatedat a national level, which has been performed in the period 2000 – 12 and applied to Europeannational data sets covering long time periods. It provides a guideline and set of best practices inthe area of time-series modelling and identifies the latest methods and applications of nationalroad safety trend analysis...
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Noise Analysis of Continuous GPS Time Series of Selected EPN Stations to Investigate Variations in Stability of Monument Types
PublicationThe type of monument that a GPS antenna is placed on plays a significant role in noise estimation for each permanent GPS station. In this research 18 Polish permanent GPS stations that belong to the EPN (EUREF Permanent Network) were analyzed using Maximum Likelihood Estimation (MLE). The antennae of Polish EPN stations are placed on roofs of buildings or on concrete pillars. The analyzed data covers a period of 5 years from 2008...
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Time series analysis and impact assessment of the temperature changes on the vegetation and the water availability: A case study of Bakun-Murum Catchment Region in Malaysia
PublicationThe Bakun-Murum (BM) catchment region of the Rajang River Basin (RRB), Sarawak, Malaysia, has been under severe threat for the last few years due to urbanization, global warming, and climate change. The present study aimed to evaluate the time series analysis and impact assessment of the temperature changes on the vegetation/agricultural lands and the water availability within the BM region. For this purpose, the Landsat data for...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Investigating the Ischaemic Phase of Skin NADH Fluorescence Dynamics in Recently Diagnosed Primary Hypertension: A Time Series Analysis
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Volterra series usefulness in modelling of the time-domain cross-talk phenomena in coupled microstrip lines with nonlinear termination
PublicationW pracy przedyskutowano możliwość wykorzystania szeregów Volterry do analizy zjawiska przesłuchu w sprzężonych liniach mikropaskowych z nieliniowym obciążeniem. Apracowano algorytm metody, zaś uzyskane wyniki numeryczne zweryfikowano poprzez porównania z wynikami badań eksperymentalnych linii obciążonych w torze transmisyjnym diodą Schottky'ego.
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublicationCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Zastosowanie analizy szeregów czasowych do oceny zanieczyszczenia powietrza atmosferycznego w rejonie Trójmiasta. Application of time series analysis on air quality assessment in the region of Tricity
PublicationNa podstawie analizy wyników pomiarów poziomów stężenia: NO3-, SO42-, F- ,Cl-, NH4+, PO43-, Ca2+, K+, Mg2+ oraz pomiarów pH i przewodności elektrolitycznej próbek wód opadowych na terenie Trójmiasta z zastosowaniem techniki analizy szeregów czasowych wykazano, że cykliczne wahania poziomów depozycji SO42-, F-, NO3- i Ca2+ w próbkach są skorelowane z cyklicznymi 9 zmianami przeważających kierunków wiatrów. Analiza struktury szeregów...
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Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
PublicationThe dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail...
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Development of cluster analysis methodology for identification of model rainfall hyetographs and its application at an urban precipitation field scale
PublicationDespite growing access to precipitation time series records at a high temporal scale, in hydrology, and particularly urban hydrology, engineers still design and model drainage systems using scenarios of rainfall temporal distributions predefined by means of model hyetographs. This creates the need for the availability of credible statistical methods for the development and verification of already locally applied model hyetographs....
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublicationTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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Examining Statistical Methods in Forecasting Financial Energy of Households in Poland and Taiwan
PublicationThis paper examines the usefulness of statistical methods in forecasting the financial energy of households. The study’s objective is to create the innovative ratios that combine both financial and demographic information of households and implement them in the forecasting models. To conduct this objective, six forecasting models are developed using three different methods—discriminant analysis, logit analysis, and decision trees...
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Studies of the Interaction Dynamics in Albumin-Chondroitin Sulfate Systems by Recurrence Method
PublicationThe physicochemical basis of lubrication of articular cartilage is still not fully understood. However, the synergy between components of the synovial fluid can be a crucial factor that could explain this phenomenon. This work presents a nonlinear data analysis technique named the recurrence method, applied to the system involving two components of synovial fluid: albumin and chondroitin sulfate (CS) immersed in a water environment....
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A Simplified Method of Trend Removal to Determine Noise Observed During a Supercapacitor’s Discharging
PublicationIn this paper, new method of trend removal is proposed. This is a simplified method based on Empirical Mode Decomposition (EMD). The method was applied for voltage time series observed during supercapacitor discharging process. It assured the determination of an additive noise component after subtracting the identified trend component. We analyzed voltage time series observed between the terminals of the supercapacitor when discharged...
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Time Delay Estimation in Two-Phase Flow Investigation Using the γ-Ray Attenuation Technique.
PublicationTime delay estimation is an important research question having many applications in a range of technologies. Measurement of a two-phase flow in a pipeline or an open channel using radioisotopes is an example of such application. For instance, the determination of velocity of dispersed phase in that case is based on estimation of the time delay between two stochastic signals provided by scintillation probes. The proper analysis...
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The Verification of the Usefulness of Electronic Nose Based on Ultra-Fast Gas Chromatography and Four Different Chemometric Methods for Rapid Analysis of Spirit Beverages
PublicationSpirit beverages are a diverse group of foodstuffs. They are very often counterfeited which cause the appearance of low quality products or wrongly labelled products on the market. It is important to find a proper quality control and botanical origin method enabling the same time preliminary check of the composition of investigated samples, which was the main goal of this work. For this purpose, the usefulness of electronic nose...
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Combined analysis of whole human blood parameters by Raman spectroscopy and spectral-domain low-coherence interferometry
PublicationIn this article the simultaneous investigation of blood parameters by complementary optical methods, Raman spectroscopy and spectral-domain low-coherence interferometry, is presented. Thus, the mutual relationship between chemical and physical properties may be investigated, because low-coherence interferometry measures optical properties of the investigated object, while Raman spectroscopy gives information about its molecular...
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Use of numerical methods in the analysis of traction energy systems—an overview of the practical examples
PublicationA characteristic feature of trolleybus transport is the random nature of traffic caused by congestion. It predestinates statistical and numerical methods for the analysis of trolleybus energy system. There are presented 3 methods of trolleybus traction system analysis: simulation of supply system based on Monte Carlo method, analysis of energy recovery potential based on statistical data analysis and benchmark of trolleybus supply...
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A Comprehensive Approach to Azo Dichlorotriazine Dye Treatment: Assessing the Impact of Physical, Chemical, and Biological Treatment Methods through Statistical Analysis of Experimental Data
PublicationThis exploration investigates integrated treatment systems combining advanced oxidation processes (Fenton and photo-Fenton) with biological methods for the effective elimination of stubborn organic compounds in simulated textile wastewater composed of azo Dichlorotriazine dye. A comprehensive optimization of key process factors including catalyst dosage, hydrogen peroxide quantity, irradiation duration, etc. was systematically...
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Hydrogen embrittlement of X2CrNiMoCuN25-6-3 super duplex stainless steel welded joints under cathodic protection
PublicationThe effect of cathodic polarization conditions on hydrogen degradation of X2CrNiMoCuN25-6-3 super duplex stainless steel welded joints, obtained using flux cored arc and submerged arc welding methods, was evaluated. Slow strain rate tensile tests of base material and welded specimens, ferrite content measurements, scanning electron microscopy observations, and statistical analysis were performed. It was found that hydrogenation...
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Global and regional economic inequality: Methods of measurement and evidences
PublicationThe lack of countries’ statistical income data, comparable across countries and years, seems to be the main reason of controversial conjectures concerning global inequality and its evolution over time. In the databases, which purport to collect income data on a worldwide scale, only some summary statistics (quantile income shares, means, Gini indices) are presented. Therefore, the development of efficient methods of extracting...
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Employing a biofeedback method based on hemispheric synchronization in effective learning
PublicationIn this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual...