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Search results for: NEURAL INFORMATION RETRIEVAL
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Automatic labeling of traffic sound recordings using autoencoder-derived features
PublicationAn approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted...
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PRINCIPLES OF ARTIFICIAL INTELLIGENCE APPLICATION IN CONTROL OF THE ENTERPRISE
PublicationThe implementation of the tasks of evaluating historical financial information, the control or audit of business activities are based primarily on professional judgments about the object of study of a professional accountant or auditor. Their findings are drawn on the basis of the study of documents, the use of audit evidence, risk assessment, etc. There is always a probability (and rather high) that professional judgment will...
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Automatic music set organizatio based on mood of music / Automatyczna organizacja bazy muzycznej na podstawie nastroju muzyki
PublicationThis work is focused on an approach based on the emotional content of music and its automatic recognition. A vector of features describing emotional content of music was proposed. Additionally, a graphical model dedicated to the subjective evaluation of mood of music was created. A series of listening tests was carried out, and results were compared with automatic mood recognition employing SOM (Self Organizing Maps) and ANN (Artificial...
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Document Agents with the Intelligent Negotiations Capability
PublicationThe paper focus is on augmenting proactive document-agents with built -in intelligence to enable them to recognize execution context provided by devices visited durning the business process, and to reach collaboration agreement despite of their conflicting requirements. We propose a solution based on neural networks to improve simple multi-issue negotiation between the document and the device, practically with no excessive cost...
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Automatic Detection and Monitoring of Cyanobacterial Blooms in the Context of the Marine Cadastre
PublicationIn the wake of the European and global spatial data infrastructures (SDI) it is important to build information systems which use and serve thematic data in compliance with the INSPIRE Directive. In the context of hydrographic data, the Directive requires EU member states to collect and share information on maritime areas divided into regions and sub-regions, as well as coastal zone management areas. These data are part of recently...
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Infobrokerstwo w Polsce.
PublicationPrzełom XX i XXI wieku stał się bezsprzecznie wiekiem informacji, sama informacja natomiast najważniejszym zasobem gospodarczym dzisiejszych przedsiębiorstw. Rozwój technologii informacyjnych i komunikacyjnych, powszechność dostępu i nieograniczony przyrost publikacji, powoduje niekontrolowany rozrost zasobów informacyjnych. Odpowiedzią na smog informacyjny jest powstanie nowego zawodu - brokera informacji, który jest pośrednikiem...
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Decision making techniques for electronic communication: an example for Turkey
PublicationCommunication is the way for people exchanging information with each other by using various tools. Electronic communication or Ecommunication is the process of sending, receiving and processing information or messages electronically. Electronic communication that is closely related to the development levels of countries, has made considerable progress especially in terms technology, innovation and entrepreneur. In this study, it...
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublicationThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...
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Sztuczne sieci neuronowe oraz metoda wektorów wspierających w bankowych systemach informatycznych
PublicationW artykule zaprezentowano wybrane metod sztucznej inteligencji do zwiększania efektywności bankowych systemów informatycznych. Wykorzystanie metody wektorów wspierających czy sztucznych sieci neuronowych w połączeniu z nowoczesną technologią mikroprocesorową umożliwia znaczący wzrost konkurencyjności banku poprzez dodanie nowych funkcjonalności. W rezultacie możliwe jest także złagodzenie skutków kryzysu finansowego.
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SOLAP GIS in maritime research
PublicationMultidimensional Geographical Information System is a system especially designed to acquire, distribute, analyze and visualize complicated spatio-temporal data. Modern Geographical Information System technology can provide easy-to-use, near real-time solutions to many problems from different areas of research. In the article, authors summarize recent works on Spatial Online Analytical Processing (SOLAP) and multidimensional Geographical...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublicationPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
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Semantic segmentation training using imperfect annotations and loss masking
PublicationOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
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Control of the cultivation of cartilages for using in the biobearings.
PublicationBiotribologiczne charakterystyki biołożysk są zależne od procesu hodowli żywej tkanki chrząstki w bioreaktorze. Z kolei proces ten, jest wielowymiarowym procesem dynamicznym sterowanym za pomocą odpowiedniego układu automatycznej regulacji. Praca przedstawia prawo i algorytm sterowania takiego procesu. W tym celu zastosowano sztuczne sieci neuronowe (Artificial Neural Networks - ANN) i zaprezentowano wyniki obliczeń.
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Fake News: Possibility of Identification in Post-Truth Media Ecology System
PublicationThe main aim of the article is identification of the attitudes towards the processes of identification and verification of fake news in the environment of digital media. The subject of the research refers to the users’ attitudes towards fake news. As indicated by the research, the attitudes towards fake news are not unambiguous. About 2/3 of the respondents claim that they are not able to distinguish fake news from true information;...
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Organisational Competence vs Transferability of Knowledge in Cluster Organisations and Technology Parks
PublicationPurpose. The main paper aims to evaluate the impact of organisational competence on knowledge and information flows within cluster organisations and technology parks, with particular emphasis on innovative content knowledge. The paper addresses the research question: “What set of competencies of cooperating companies allows access to information and knowledge in cluster and parks structures?" Methodology. The authors report their...
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Simulating Malware with MAlSim
PublicationThis paper describes MAlSim - Mobile Agent Malware Simulator - a mobile agent framework developed to address one of the most important problems related to the simulation of attacks against information systems i.e. the lack of adequate tools for reproducing behaviour of malicious software (malware). The framework can be deployed over the network of an arbitrary information system and it aims at simulating behaviour of each instance...
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Simulating malware with MAlSim
PublicationThis paper describes MAlSim - Mobile Agent Malware Simulator - a mobile agent framework developed to address one of the most important problems related to the simulation of attacks against information systems, i.e. the lack of adequate tools for reproducing behaviour of malicious software (malware). The framework can be deployed over the network of an arbitrary information system and it aims at simulating behaviour of each instance...
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Wykorzystanie sztucznych sieci neuronowych do szacowania wpływu drgań na budynki jednorodzinne
PublicationW artykule przedstawiono metodę prognozowania wpływu drgań na budynki mieszkalne z wykorzystaniem sztucznych sieci neuronowych. Drgania komunikacyjne mogą doprowadzić do uszkodzenia elementów konstrukcyjnych, a nawet do awarii budynku. Najczęstszym efektem są jednak rysy, pękanie tynku i wypraw. Metody oparte na sztucznej inteligencji są przybliżone, ale stanowią wystarczająco dokładną i ekonomiczną alternatywę dla tradycyjnych...
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A method of self-testing of analog circuits based on fully differential op-amps with theTCBF classifier
PublicationA new approach of self-testing of analog circuits based on fully differential op-amps of mixed-signal systems controlled by microcontrollers is presented. It consists of a measurement procedure and a fault diagnosis procedure. We measure voltage samples of a time response of a tested circuit on a stimulation of a unit step function given at the common-mode reference voltage input of the op-amp. The fault detection and fault localization...
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Adaptive CAD-Model Construction Schemes
PublicationTwo advanced surrogate model construction techniques are discussed in this paper. The models employ radial basis function (RBF)interpolation scheme or artificial neural networks (ANN) with a new training algorithm. Adaptive sampling technique is applied withrespect to all variables. Histograms showing the quality of the models are presented. While the quality of RBF models is satisfactory, theperformance of the ANN models obtained...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublicationThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Faults and Fault Detection Methods in Electric Drives
PublicationThe chapter presents a review of faults and fault detection methods in electric drives. Typical faults are presented that arises for the induction motor, which is valued in the industry for its robust construction and cost-effective production. Moreover, a summary is presented of detectable faults in conjunction with the required physical information that allow a detection of specific faults. In order to address faults of a complete...
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Experimental and Theoretical Screening for Green Solvents Improving Sulfamethizole Solubility
PublicationSolubility enhancement of poorly soluble active pharmaceutical ingredients is of crucial importance for drug development and processing. Extensive experimental screening is limited due to the vast number of potential solvent combinations. Hence, theoretical models can offer valuable hints for guiding experiments aimed at providing solubility data. In this paper, we explore the possibility of applying quantum-chemistry-derived...
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The role of EMG module in hybrid interface of prosthetic arm
PublicationNearly 10% of all upper limb amputations concern the whole arm. It affects the mobility and reduces the productivity of such a person. These two factors can be restored by using prosthetics. However, the complexity of human arm makes restoring its basic functions quite difficult. When the osseointegration and/or targeted muscle reinnervation (TMR) are not possible, different modalities can be used to control the prosthesis. In...
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Preserving Trees in Automata
PublicationWe present a method to store additional information in a minimal automaton so that it is possible to compute a corresponding tree node number for a state. The number can then be used to retrieve additional information. The method works for minimal (and any other) deterministic acyclic finite state automata (DFAs). We also show how to compute the inverse mapping.
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Metody sztucznej inteligencji do wspomagania bankowych systemów informatycznych
PublicationW pracy opisano zastosowania nowoczesnych metod sztucznej inteligencji do wspomagania bankowych systemów informatycznych. Wykorzystanie w systemach informatycznych algorytmów ewolucyjnych, harmonicznych, czy sztucznych sieci neuronowych w połączeniu z nowoczesną technologią mikroprocesorową umożliwiają zasadniczy wzrost konkurencyjności banku. Dlatego w pracy omówiono wybrane zastosowania bankowe ze szczególnym uwzględnieniem zbliżeniowych...
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Wireless paging system
PublicationAssistance to patients at hospitals and nursing homesoften encounters problems related to obtaining information onthe current needs of the patient. Traditionally, patient informshospital stuff by wire and wireless paging systems. WirelessPaging Systems allow one to overcome the limitations of theirwire counterparts, which include high installation costs (cabling)and lack of patient mobility. The main difference betweenpresented...
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Creating a Realible Music Discovery and Recomendation System
PublicationThe aim of this paper is to show problems related to creating a reliable music dis-covery system. The SYNAT database that contains audio files is used for the purpose of experiments. The files are divided into 22 classes corresponding to music genres with different cardinality. Of utmost importance for a reliable music recommendation system are the assignment of audio files to their appropriate gen-res and optimum parameterization...
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Determination of impurities in pharmaceutical products using LC-MS
PublicationPharmaceutical products can be contaminated by residues of solvents, reagents (used for the synthesis) or degradation products. Impurities in drug may pose a risk to human health and life, therefore analysis and identification of impurities in pharmaceutical products is veryimportant and inevitable.High performance liquid chromatography coupled with mass spectrometry (MS) is very useful technique for identification impurities in...
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Determination of chlorine concentration using single temperature modulated semiconductor gas sensor
PublicationA periodic temperature modulation using sinusoidal heater voltage was applied to a commercial SnO2 semiconductor gas sensor. Resulting resistance response of the sensor was analyzed using a feature extraction method based on Fast Fourier Transformation (FFT). The amplitudes of the higher harmonics of the FFT from the dynamic nonlinear responses of measured gas were further utilized as an input for Artificial Neural...
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Knowledge representation of motor activity of patients with Parkinson’s disease
PublicationAn approach to the knowledge representation extraction from biomedical signals analysis concerning motor activity of Parkinson disease patients is proposed in this paper. This is done utilizing accelerometers attached to their body as well as exploiting video image of their hand movements. Experiments are carried out employing artificial neural networks and support vector machine to the recognition of characteristic motor activity...
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A Method for Optimising the Blade Profile in Kaplan Turbine
PublicationThis paper introduces a method of blade profile optimisation for Kaplan-type turbines, based on modelling the interaction between rotor and stator blades. Rotor and stator blade geometry is described mathematically by means of a midline curve and thickness distribution. Genetic algorithms are then used to find a global optimum that minimises the loss coefficient. This allows for variety of possible blade shapes and configurations....
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Selection of Features for Multimodal Vocalic Segments Classification
PublicationEnglish speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...
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AUTOMATED NEGOTIATIONS OVER COLLABORATION PROTOCOL AGREEMENTS
PublicationThe dissertation focuses on the augmentation of proactive document - agents with built-in intelligence to recognize execution context provided by devices visited during a business process, and to reach collaboration agreement despite conflicting requirements. The proposed solution, based on intelligent bargaining using neural networks to improve simple multi-issue negotiation between the document and thedevice, requires practically...
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Fluctuation-Enhanced Sensing
PublicationFluctuation-enhanced sensing (FES) is an exciting and relatively new research field that promises to extend the range of information that can be extracted from a single sensor. In FES, the stochastic fluctuations of the sensor signal, rather than its average value, are recorded and analyzed. Typical components of such fluctuations are due to interactions at the microscopic level. Proper statistical analysis provides optimum sensory...
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The aluminium and polycarbonate covering to the roof over the stadium in Gdańsk
PublicationThis paper presents information about structural elements of the roof covering to the stadium in Gdansk built for the 2012 European Football Championship in Poland and the Ukraine. The paper discusses elements of the polycarbonate covering, the supporting structure and the drainage system. It also provides information about tests and research performed prior to construction, which determined the solutions adopted as well as...
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Down-Sampling of Large LiDAR Dataset in the Context of Off-Road Objects Extraction
PublicationNowadays, LiDAR (Light Detection and Ranging) is used in many fields, such as transportation. Thanks to the recent technological improvements, the current generation of LiDAR mapping instruments available on the market allows to acquire up to millions of three-dimensional (3D) points per second. On the one hand, such improvements allowed the development of LiDAR-based systems with increased productivity, enabling the quick acquisition...
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General concept of reduction process for big data obtained by interferometric methods
PublicationInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...
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Accurate Lightweight Calibration Methods for Mobile Low-Cost Particulate Matter Sensors
PublicationMonitoring air pollution is a critical step towards improving public health, particularly when it comes to identifying the primary air pollutants that can have an impact on human health. Among these pollutants, particulate matter (PM) with a diameter of up to 2.5 μ m (or PM2.5) is of particular concern, making it important to continuously and accurately monitor pollution related to PM. The emergence of mobile low-cost PM sensors...
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Application of autoencoder to traffic noise analysis
PublicationThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublicationRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Machine Learning Techniques in Concrete Mix Design
PublicationConcrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which...
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Quantum mechanical which-way experiment with an internal degree of freedom
PublicationFor a particle travelling through an interferometer, the trade-off between the available which-way information and the interference visibility provides a lucid manifestation of the quantum mechanical wave-particle duality. Here we analyse this relation for a particle possessing an internal degree of freedom such as spin. We quantify the trade-off with a general inequality that paints an unexpectedly intricate picture of wave-particle...
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Wroclaw University of Technology Knowledge Repository - project objectives
PublicationKnowledge Repository is a project created in the Library and Scientific Information Centre of Wroclaw University of Technology (WrUT). Its main task will be collecting, sharing, and promoting scientific publications of researchers, postgraduates and students of WrUT. It will be also used for bibliometric analysis and reporting research output of WrUT scientific community.Knowledge Repository will closely cooperate with other databases...
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Event-Triggered Communication in Cooperative, Adaptive Model Predictive Control of a Nuclear Power Plant’s Turbo–Generator Set
PublicationThis paper discusses the issue of optimizing the communication between the components of a cooperating control system formed by a pair of MPC controllers of a nuclear power plant turbine set using online recursive least squares identification. It is proposed to use event-triggered communication, i.e., sending information only at selected time instants, as opposed to the standard approach where communication is triggered by time...
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Reactivation of seizure‐related changes to interictal spike shape and synchrony during postseizure sleep in patients
PublicationOBJECTIVE: Local field potentials (LFPs) arise from synchronous activation of millions of neurons, producing seemingly consistent waveform shapes and relative synchrony across electrodes. Interictal spikes (IISs) are LFPs associated with epilepsy that are commonly used to guide surgical resection. Recently, changes in neuronal firing patterns observed in the minutes preceding seizure onset were found to be reactivated during postseizure...
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Dekodowanie kodów iterowanych z użyciem sieci neuronowej
PublicationNadmiarowe kody iterowane są jedną z prostych metod pozyskiwania długich kodów korekcyjnych zapewniających dużą ochronę przed błędami. Jednocześnie, chociaż ich podstawowy iteracyjny dekoder jest prosty koncepcyjnie oraz łatwy w implementacji, to nie jest on rozwiązaniem optymalnym. Poszukując alternatywnych rozwiązań zaproponowano, przedstawioną w pracy, strukturę dekodera tego typu kodów wspomaganą przez sieci neuronowe. Zaproponowane...