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Improved Architecture and the Synthesis Algorithm for Bithreshold Neural Network Classifier 18

Improved Architecture and the Synthesis Algorithm for Bithre...

引用

18th IEEE International Conference on Computer Science and information Technologies, CSIT 2023

作者： Kotsovsky, Vladyslav Batyuk, Anatoliy Uzhhorod National University Department of Information Management Systems and Technologies Uzhhorod Ukraine Lviv Polytechnic National University Department of Automated Control Systems Lviv Ukraine

ISBN: (纸本)9798350360462

The model of the 3-layer feed-forward neural network is introduced whose first hidden layer consists of bithreshold neurons and the other layers - of single-threshold ones. The proposed network is capable to recognize compact finite set of patterns using a union of hyperrectangular decision regions in n-dimensional space. We design a multiclass classifier on the base of such network, propose the synthesis algorithm for it and estimate the networks size as well as the time of computations. The simulation results demonstrate that the application of the additional hidden layer improves the accuracy of classification. © 2023 IEEE.

关键词： Multilayer neural networks

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Multithreshold Neural Units and Networks 18

Multithreshold Neural Units and Networks

引用

18th IEEE International Conference on Computer Science and information Technologies, CSIT 2023

ISBN: (纸本)9798350360462

We deal with theoretical issues concerning the application of the multithreshold architecture in the theory of neural computation. The way of representing a multithreshold function by 2-layer neural network consisting of single-threshold neural units with equal weights is established in the paper. We also study the complexity of the problem of the learning k-threshold neurons and prove that this problem is NP-hard if the number of thresholds is greater than one. © 2023 IEEE.

关键词： Neural networks

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Method to Detect Slag Flow in Course of Steel Casting Based on Machine Learning Algorithms 4

Method to Detect Slag Flow in Course of Steel Casting Based ...

引用

4th International Conference on control systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2022

作者： Tsygankov, Yury Kovriznich, Yury Smirnov, Dmitry Poleshchenko, Dmitry Nust 'MISIS' Automated and Information Control Systems Department Stary Oskol Russia

ISBN: (数字)9781665456593

ISBN: (纸本)9781665456593

The paper considers the possibility of implementing a system capable of identifying the ingress of slag into the intermediate ladle at an earlier stage of casting. To do this., it is proposed to analyze the vibration acceleration signal measured on the steel filling unit by a neural network with an autoencoder architecture to determine the moment when the slag starts to flow out of the steel filling ladle and transfer it to the control system © 2022 IEEE.

关键词： Steel castings

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Simulation Model for controlling the processing of information Packets by a NoC Router 7

Simulation Model for Controlling the Processing of Informati...

引用

7th International Conference on information, control, and Communication Technologies, ICCT 2023

作者： Kutuzov, Denis Osovsky, Alexey Starov, Dmitriy Maltseva, Nataliya Esaulenko, Vladimir Astrakhan State Technical Universitet Dept. of Communication Astrakhan Russia Astrakhan State Technical Universitet Dept. of Automated Information Processing and Control Systems Astrakhan Russia

ISBN: (纸本)9798350340945

This article describes the challenges of modeling switch fabric traffic that is part of NoC routers. Simulation is often used to validate a NoC design and identify potential performance bottlenecks before implementing hardware. Due to the distributed and complex network topology of routers, arbitration and routing algorithms, etc., timing, buffer queuing, and hence infrastructure performance are difficult to predict. Network traffic also generates application traffic in data processing nodes. When processing NoC traffic, the activity of IP cores is unstable and does not have stationarity, so it is very important to find traffic control mechanisms. Often, well-known models built on the basis of queuing theory do not always correctly reflect the connection request processing logic, do not take into account deadlocks and other features of the system functioning. An approach that can more accurately take into account the nuances of the switch is to build an agent-based model. To create it, we used the Mesa framework implemented in the Python programming language. The switch has small built-in buffers - one for each input. The model used a switch with 5 inputs and 5 outputs. The idea behind switch traffic management is to count how often there are transacts in the internal buffers that are directed to one exit. If they occur frequently enough, then the information flow is split and two or more outputs are given the same identifier to service such transacts in parallel. © 2023 IEEE.

关键词： Network-on-chip

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Prediction of the Magnitude of Lightning Impulse Interference in an Electronic Device Using an Artificial Neural Network

Prediction of the Magnitude of Lightning Impulse Interferenc...

引用

2024 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024

作者： Gizatullin, Zinnur Mubarakov, Ramis Kazan National Research Technical University Named After A.N. Tupolev-KAI Department For Automated Systems For Information Processing And Control Department For Computer-Aided Design Systems Kazan Russia Kazan National Research Technical University Named After A.N. Tupolev-KAI Department For Computer-Aided Design Systems Kazan Russia

ISBN: (纸本)9798350395013

Reliable operation of modern electronic devices is the basis for their effective use. Electromagnetic interference, such as lightning, creates the risk of temporary or permanent disruption of the functioning of device elements. Therefore, it is necessary to take into account the possible consequences of such interference on the basis of prediction even at the design stage of electronic devices. The paper a technique for predicting the magnitude of lightning impulse interference in electronic devices using an artificial neural network is proposed. The advantage of this approach over simulation modeling is that rather complex three-dimensional models and long computation times are not needed. A stand was developed and obtained by measuring the amount of lightning interference in an electronic device. The features of the task of training an artificial neural network based on experimental data are considered. The architecture and parameters of the artificial neural network have been selected. An artificial neural network was trained based on experimental data. The root mean square error between the predicted data and the average impulse interference voltage values on the training data does not exceed acceptable values. The results of predicting the magnitude of lightning interference in an electronic device are presented. If we consider further prospects for using an artificial neural network to predict electromagnetic interference, we can note the relevance of the problem of the impact of electrostatic discharge, intentional short pulse and etc. © 2024 IEEE.

关键词： Neural networks

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Technique for Research of Conducted Interference from Power Converters in Operating Conditions

Technique for Research of Conducted Interference from Power ...

引用

2022 International Russian Automation Conference, RusAutoCon 2022

作者： Gizatullin, Zinnur Mubarakov, Ramis Kazan National Research Technical University Named after A.N. Tupolev-KAI Department for Automated Systems for Information Processing and Control Kazan Russia

ISBN: (数字)9781665466554

ISBN: (纸本)9781665466554

An important task for the reliable functioning of control systems is to study and improve the noise immunity of its electronic devices. An experimental technique and a measuring sensor for research of conducted interference from power converters are proposed. The technique does not imply accurate measurement and evaluation of the absolute values of interference. It allows you to explore the relative change in the magnitude of conducted interference in the field of operation of devices. An increase in conducted interference occurs when a new possible source is added. This approach makes it possible to identify ways to reduce interference and evaluate the effectiveness of the measures taken. A test example with a switching power supply is presented. The proposed tools are well suited for the study of conducted interference on board the aircraft when modernization by adding new power converters. © 2022 IEEE.

关键词： Flight control systems

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Image Denoising Using Weight Model

Image Denoising Using Weight Model

引用

2022 International Russian Automation Conference, RusAutoCon 2022

作者： Shleymovich, Mikhail Safina, Rimma Kazan National Research Technical University Named after A.N. Tupolev-KAI Department for Automated Systems for Information Processing and Control Kazan Russia

ISBN: (数字)9781665466554

ISBN: (纸本)9781665466554

The article deals with the issues of primary image processing in computer vision-based systems. The main approaches to solving the problems of image enhancement and restoration, including using wavelet transformations, are described. Filtering algorithms based on threshold processing of the detailing coefficients at various levels of the wavelet decomposition are considered. An approach is proposed based on the construction and analysis of a weight model that reflects the importance of image elements in terms of their contribution to the total energy. A method for constructing a multiscale weight model, a procedure for removing noise in an image using it, and the results of experiments on processing noisy test images are given. It is shown that using the proposed procedure, it is possible to ensure the removal of Gaussian noise with a large standard deviation value. © 2022 IEEE.

关键词： Image reconstruction

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Research the Radiated Electromagnetic Interference from Power Converters under Operating Conditions

Research the Radiated Electromagnetic Interference from Powe...

引用

2022 International Russian Automation Conference, RusAutoCon 2022

作者： Gizatullin, Zinnur Lyasheva, Stella Kazan National Research Technical University Named after A.N. Tupolev-KAI Department for Automated Systems for Information Processing and Control Kazan Russia

ISBN: (数字)9781665466554

ISBN: (纸本)9781665466554

Noise immunity issues are always a potential problem for the reliable functioning of control and automation systems. Modern electronic devices generally meet the requirements for electromagnetic interference when considered separately. But usually they are part of the control system in a complex technical facility. Then undefined ways and mechanisms of interaction of interferences from various systems may arise. The article proposes a technique and means for research radiated electromagnetic interference from power converters under operating conditions. As an example, the application of the created tools for a switching power supply is considered. The conclusions are presented on the basis of the analysis of the obtained results. © 2022 IEEE.

关键词： Electromagnetic pulse

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Adaptive Machine Learning Methods in Oil Well Research

Adaptive Machine Learning Methods in Oil Well Research

引用

2023 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2023

作者： Mokshin, Vladimir Kychkin, Ivan Minigaliev, Ainur Kazan National Research Technical University Named after A. N. Tupolev - Kai Department of Automated Information Processing Systems and Management Kazan Russia

ISBN: (纸本)9781665475952

This article discusses the oil well exploration model using neural networks and prediction in Python. The problem of identifying significant features is considered. Decision tree algorithms, Sequential Forward Selection (SFS), Sequential Backward Selection (SBS) and Exhaustive Feature Selection (EFS) are considered as selection methods. Graphs are presented illustrating comparisons of methods and results of algorithms, and an assessment of the quality of methods is also considered. The paper considers several types of neural networks for building an oil well survey model based on learning methods: the Levenberg-Marquardt method, the Bayesian regularization method, the error backpropagation method. The results of evaluating effective performance indicators from the above teaching methods and methods for highlighting significant features are shown. © 2023 IEEE.

关键词： Python

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Investigation of Machine Learning Methods for Stroke Prediction 9

Investigation of Machine Learning Methods for Stroke Predict...

引用

9th IEEE International Conference on information Technology and Nanotechnology, ITNT 2023

作者： Faskhutdinova, Alina Grigorieva, Daria Garafutdinov, Bulat Mokshin, Vladimir University Named after A. N. Tupolev - Kai Processing Systems and Management Kazan National Research Technical Department of Automated Information Kazan Russia

ISBN: (纸本)9798350397338

This article discusses methods for predicting stroke. It has been shown that there are different methods for solving the problem. The article presents a description of the developed model for predicting the likelihood of stroke. The system allows for a quick diagnosis of this disease based on a small number of input parameters. Several methods for implementing machine learning have been considered. The method of support vectors SVM (Support Vector Machine) was taken as a basis. © 2023 IEEE.

关键词： Forecasting

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