Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923264
A. V. Kurbako, V. V. Skazkina, E. Borovkova, A. Karavaev
We have developed four real-time methods for calculating a cardiointervalogram from a photoplethysmogram signal to calculate the total percentage of phase synchronization for estimating the state of the cardiovascular system. The methods were compared with the classical method of calculating a cardiointervalogram from an electrocardiogram signal using signals recorded from healthy volunteers and patients with COVID-19.
{"title":"Development of Real-Time Methods for Calculating Cardiointervalograms for Estimating the State of the Cardiovascular System Using a Single Photoplethysmogram Signal","authors":"A. V. Kurbako, V. V. Skazkina, E. Borovkova, A. Karavaev","doi":"10.1109/DCNA56428.2022.9923264","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923264","url":null,"abstract":"We have developed four real-time methods for calculating a cardiointervalogram from a photoplethysmogram signal to calculate the total percentage of phase synchronization for estimating the state of the cardiovascular system. The methods were compared with the classical method of calculating a cardiointervalogram from an electrocardiogram signal using signals recorded from healthy volunteers and patients with COVID-19.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127939298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923146
V. Skazkina, Konstantin Popov, A. Kurbako
The work aims to study the dynamics of connections between the circuits of the autonomic regulation of blood circulation in patients with Covid-19. The tools for the study are methods of nonlinear analysis. The work shows dynamics of the degree of phase synchronization between 0.1-Hz components of the RR-interval signals and the photoplethysmogram, and no visible change in the direction of connections.
{"title":"Dynamics of connections between autonomic regulatory circuits of the cardiovascular system in patients with Covid-19","authors":"V. Skazkina, Konstantin Popov, A. Kurbako","doi":"10.1109/DCNA56428.2022.9923146","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923146","url":null,"abstract":"The work aims to study the dynamics of connections between the circuits of the autonomic regulation of blood circulation in patients with Covid-19. The tools for the study are methods of nonlinear analysis. The work shows dynamics of the degree of phase synchronization between 0.1-Hz components of the RR-interval signals and the photoplethysmogram, and no visible change in the direction of connections.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123389426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923181
A. Fradkov, A. Semenov
In this paper we set and solve the problem of functional identification of parameters of the Lotka-Volterra multispecies model using the ”Stripe” algorithm developed by V.A. Yakubovich. Assertions about some properties of the model are formulated and proved. The theoretical results are supported by modeling.
{"title":"Functional identification of the parameters multispecies Lotka-Volterra model","authors":"A. Fradkov, A. Semenov","doi":"10.1109/DCNA56428.2022.9923181","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923181","url":null,"abstract":"In this paper we set and solve the problem of functional identification of parameters of the Lotka-Volterra multispecies model using the ”Stripe” algorithm developed by V.A. Yakubovich. Assertions about some properties of the model are formulated and proved. The theoretical results are supported by modeling.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115251763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923278
O. Shagniev, A. Fradkov
This paper is devoted to the study of the influence of digitalization and discretization on the speed gradient algorithm operation for the multiple synchronization control of vibration setup rotors. The paper presents results of numerical simulation based on the system dynamics equations and approximate values of vibration setup parameters. The simulation results show that an increase of the discretization sampling step leads to a disruption of the multiple synchronization mode up to the stability loss.
{"title":"Discretization Effects in Speed-Gradient Two-rotor Vibration Setup Synchronization Control","authors":"O. Shagniev, A. Fradkov","doi":"10.1109/DCNA56428.2022.9923278","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923278","url":null,"abstract":"This paper is devoted to the study of the influence of digitalization and discretization on the speed gradient algorithm operation for the multiple synchronization control of vibration setup rotors. The paper presents results of numerical simulation based on the system dynamics equations and approximate values of vibration setup parameters. The simulation results show that an increase of the discretization sampling step leads to a disruption of the multiple synchronization mode up to the stability loss.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114284302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923229
Kseniya Mirzaeva, Artem Badarin, V. Antipov, V. Grubov, A. Hramov
Modern education in the digital reality of the 21st century has great potential to use various strategies to personalize the learning process in order to improve the teaching system. Here, important tasks is an objective assessment of the psycho-physiological state of the child in the learning process and the development of the pedagogical concept of using the data obtained to personalize the learning of elementary school students. The current study proposes the design of a neurophysiological experiment aimed at studying the cognitive and executive functions of primary school children. Tasks aimed at visual search, working memory and mental arithmetic are proposed as testing elementary cognitive functions.
{"title":"Experimental design for studying brain activity and behavior of a child in the process of solving elementary cognitive tasks","authors":"Kseniya Mirzaeva, Artem Badarin, V. Antipov, V. Grubov, A. Hramov","doi":"10.1109/DCNA56428.2022.9923229","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923229","url":null,"abstract":"Modern education in the digital reality of the 21st century has great potential to use various strategies to personalize the learning process in order to improve the teaching system. Here, important tasks is an objective assessment of the psycho-physiological state of the child in the learning process and the development of the pedagogical concept of using the data obtained to personalize the learning of elementary school students. The current study proposes the design of a neurophysiological experiment aimed at studying the cognitive and executive functions of primary school children. Tasks aimed at visual search, working memory and mental arithmetic are proposed as testing elementary cognitive functions.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131418501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923235
I. Zaitceva, B. Andrievsky
Controller tuning is a standard engineering task. To quickly adjust the controller settings in real-time, it becomes necessary to use intelligent control algorithms. In this paper, we propose an approach to tuning the speed controller of a vibration machine, which will ensure its maximum performance, using the reinforcement learning method. In this context of problem solving, the policy is presented in a parametric family of controller gains. In this case, the agent interacts with the virtual environment and the PI controller is implemented the software. The effectiveness of the proposed approach has been verified by real-time simulation and experiments on the two-rotor vibration unit. The advantage of the described learning algorithm is that the complex system is considered a black box. Thus, it is required to know the reference drive speed and measure the output speed.
{"title":"Real-time Reinforcement Learning of Vibration Machine PI-controller","authors":"I. Zaitceva, B. Andrievsky","doi":"10.1109/DCNA56428.2022.9923235","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923235","url":null,"abstract":"Controller tuning is a standard engineering task. To quickly adjust the controller settings in real-time, it becomes necessary to use intelligent control algorithms. In this paper, we propose an approach to tuning the speed controller of a vibration machine, which will ensure its maximum performance, using the reinforcement learning method. In this context of problem solving, the policy is presented in a parametric family of controller gains. In this case, the agent interacts with the virtual environment and the PI controller is implemented the software. The effectiveness of the proposed approach has been verified by real-time simulation and experiments on the two-rotor vibration unit. The advantage of the described learning algorithm is that the complex system is considered a black box. Thus, it is required to know the reference drive speed and measure the output speed.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125145167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923295
S. Shchanikov, I. Bordanov
Here we propose the concept of neuromorphic analog memristive vision systems. The main feature of this concept is the rejection of analog-to-digital and digital-to-analog conversions when capturing input visual data for a spiking neural network (SNN) based on memristive devices. This can be achieved by combining photodiodes and memristors and directly feeding analog pulses from the output of such a circuit to the input of a SNN circuit. This concept relates to the field of in-memory and in-sensor computing and will makes it possible to create more compact, energy-efficient visual processing units for wearable, on-board and embedded electronics for such areas as robotics, the Internet of Things, neuroprosthetics and other practical applications in the field of artificial intelligence.
{"title":"The Concept of Neuromorphic Vision Systems based on Memristive Devices","authors":"S. Shchanikov, I. Bordanov","doi":"10.1109/DCNA56428.2022.9923295","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923295","url":null,"abstract":"Here we propose the concept of neuromorphic analog memristive vision systems. The main feature of this concept is the rejection of analog-to-digital and digital-to-analog conversions when capturing input visual data for a spiking neural network (SNN) based on memristive devices. This can be achieved by combining photodiodes and memristors and directly feeding analog pulses from the output of such a circuit to the input of a SNN circuit. This concept relates to the field of in-memory and in-sensor computing and will makes it possible to create more compact, energy-efficient visual processing units for wearable, on-board and embedded electronics for such areas as robotics, the Internet of Things, neuroprosthetics and other practical applications in the field of artificial intelligence.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125661064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923218
D. M. Semenov, S. Plotnikov, Alexander L. Fradkov
The paper studies controlled synchronization in regular delay-coupled Hindmarsh-Rose network with a constant delay. It is the fact that signal propagation delays between nodes can hinder their synchronization. This investigation introduces a controller that can ensure the asymptotic synchronization between neurons in the network under study. The provided analysis is based on the Lyapunov-Krasovskii method.
{"title":"Controlled synchronization in regular delay-coupled networks of Hindmarsh-Rose neurons","authors":"D. M. Semenov, S. Plotnikov, Alexander L. Fradkov","doi":"10.1109/DCNA56428.2022.9923218","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923218","url":null,"abstract":"The paper studies controlled synchronization in regular delay-coupled Hindmarsh-Rose network with a constant delay. It is the fact that signal propagation delays between nodes can hinder their synchronization. This investigation introduces a controller that can ensure the asymptotic synchronization between neurons in the network under study. The provided analysis is based on the Lyapunov-Krasovskii method.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129340504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923243
Valentina Y. Guleva
Systems of intelligent interacting agents demonstrate high complexity of learning process due to complexity of single agent learning combined with their communication. Agent interactions are aimed at enhancing speed, quality, and complexity characterictics, nevetheless, each interaction may worse single agent results as well as enhance them. Therefore, building effective communication patterns is of high interest for learning process of intelligent systems. As an applied task, we consider project execution dynamics, where single tasks are assigned to employees having several conflicting parameters, while an intelligent system consists of multiple intelligent agents, learned by reinforcement algorithms. Different patterns of interaction according to agent similarities are explored as a factor affecting learning process. The condition of two agents connection is there similarity value, greater than some determined threshold; similarity function is determined for five static and dynamics parameters, and their influence is regulated by the corresponding five multipliers. The experiment shows there are significant parameters, showing more effect of connection on learning dynamics. This can be seen via effect of parameters, regulating neighbours contribution.
{"title":"Node Correlation Effects on Learning Dynamics in Networked Multiagent Reinforcement Learning","authors":"Valentina Y. Guleva","doi":"10.1109/DCNA56428.2022.9923243","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923243","url":null,"abstract":"Systems of intelligent interacting agents demonstrate high complexity of learning process due to complexity of single agent learning combined with their communication. Agent interactions are aimed at enhancing speed, quality, and complexity characterictics, nevetheless, each interaction may worse single agent results as well as enhance them. Therefore, building effective communication patterns is of high interest for learning process of intelligent systems. As an applied task, we consider project execution dynamics, where single tasks are assigned to employees having several conflicting parameters, while an intelligent system consists of multiple intelligent agents, learned by reinforcement algorithms. Different patterns of interaction according to agent similarities are explored as a factor affecting learning process. The condition of two agents connection is there similarity value, greater than some determined threshold; similarity function is determined for five static and dynamics parameters, and their influence is regulated by the corresponding five multipliers. The experiment shows there are significant parameters, showing more effect of connection on learning dynamics. This can be seen via effect of parameters, regulating neighbours contribution.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122374581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923221
A. Kapustnikov, M. Sysoeva, I. Sysoev
In this work, an ensemble of 28 connected neurooscillators for modeling epilepsy was considered. There were five types of neurons in this ensemble, with specific physiologically proved neuron models with physiologically reasonable parameters selected for each type of models. In addition, due to the presence of excitatory and inhibitory connections in the network, it was decided to use physiological synapse models for AMPA and GABA receptors, respectively. As a result, it was shown that such a system is capable of demonstrating long transients simulating epileptiform activity similarly to the previously considered models. This confirms the hypothesis of the network structure, key role in the occurrence of epileptic seizures, with validating this idea based on physiologically proved models and parameters and increasing the scientific significance of the underlying idea.
{"title":"Studying response to external driving in a model of thalamocortical system with specialized neuron equations","authors":"A. Kapustnikov, M. Sysoeva, I. Sysoev","doi":"10.1109/DCNA56428.2022.9923221","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923221","url":null,"abstract":"In this work, an ensemble of 28 connected neurooscillators for modeling epilepsy was considered. There were five types of neurons in this ensemble, with specific physiologically proved neuron models with physiologically reasonable parameters selected for each type of models. In addition, due to the presence of excitatory and inhibitory connections in the network, it was decided to use physiological synapse models for AMPA and GABA receptors, respectively. As a result, it was shown that such a system is capable of demonstrating long transients simulating epileptiform activity similarly to the previously considered models. This confirms the hypothesis of the network structure, key role in the occurrence of epileptic seizures, with validating this idea based on physiologically proved models and parameters and increasing the scientific significance of the underlying idea.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124049152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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