scholarly journals Data Processing of Discrete Composite Frequency-Modulated Signals by Means of the Neural Network Analysis

Author(s):  
S.N. Darovskikh ◽  
A.O. Golovenko ◽  
N.S. Nikitin
Author(s):  
Liudmyla Tereikovska

The urgency of the task of developing tools for neural network analysis of biometric parameters for recognizing the personality and emotions of students of the distance learning system has been substantiated. The necessity of formalizing the architectural solutions used in the creation of software for neural network analysis of biometric parameters is shown. As a result of the research carried out in terms of the UML modeling language, the architecture of the neural network analyzer of biometric parameters has been developed. Diagrams of options for using the neural network analyzer have been developed both for recognizing the personality of a student when entering the system, and for recognizing the personality and emotions of a student in the process of his interaction with the distance learning system. Also, based on the developed use case diagrams, a structural diagram of the analyzer is built. The necessity of including subsystems for determining the functional parameters of the analyzer, registration of biometric parameters, neural network analysis of registered biometric parameters, personality recognition and emotion recognition is substantiated. An original feature of the proposed architectural solutions is the introduction into the neural network analysis subsystem of an integrated analysis module designed to summarize the results of neural network analysis separately for each of the biometric parameters. A rule for making an integrated decision has been developed, taking into account the results of a neural network analysis of each of the registered biometric parameters and the corresponding weight coefficients determined by expert evaluation. The introduction of the integrated analysis module makes it possible to increase the accuracy of recognition of emotions and personality of a student, since the final classification is realized through a generalized assessment of several guaranteed significant biometric parameters. In addition, the use of this module makes it possible to increase the reliability of the neural network analyzer in case of difficulties associated with the registration of a particular biometric parameter. It has been established that the decision-making rule can be improved by using one or more neural networks in the integrated analysis module, designed to generalize the results of the neural network analysis of all registered biometric parameters. It is proposed to correlate the directions of further research with the development of appropriate neural network solutions.


2021 ◽  
Vol 17 (2) ◽  
pp. 361-384
Author(s):  
Valerii V. SMIRNOV

Subject. The article discusses the dynamics of the Russian indicators of administration. Objectives. I identify constraints that determine administrative criteria. Methods. The study is based on the systems approach and methods of statistical, cluster and neural network analysis. Results. The article spotlights the stewardship of Russia’s economy today and theoretical considerations on general administrative criterion. I analyzed trends in the Russian administrative indicators, referring to six general aspects of management (Worldwide Governance Indicators, World Bank Group). Using the cluster analysis of growth rates of the Russian administrative indicators, I found major and crucial clusters. Conducting the neural network analysis, I understood the hierarchy of priorities, with the governmental efficiency being the most important one. The supremacy of law, political stability and no violence/terrorism were found to of the least significance. Having evaluated the asymmetry of trends in the Russian administrative indicators against the average, I identified the priority, that us the governmental efficiency, which turns to be a determining criterion of management. Conclusions and Relevance. As a result of the study, I understood what hampers the dynamics of the Russian administrative indicators by determining administrative criteria. I especially point out the possibility of raising the governmental efficiency to maintain the political stability and prevent violence/terrorism by neglecting the supremacy of law, regulatory quality and simulating the anti-corruption activity. The findings contribute to the necessary scope of governmental authorities’ competence to make administrative decisions on the effective stewardship of Russia.


Author(s):  
Ilya Germashev ◽  
◽  
Evgeniya Derbisher ◽  
Vyacheslav Derbisher ◽  
Elena Markushevskaya ◽  
...  

Author(s):  
Jancikova Zora ◽  
Bosak Ondrej ◽  
Zimny Ondrej ◽  
Legouera Messaoud ◽  
Minarik Stanislav ◽  
...  

2017 ◽  
Vol 5 (1) ◽  
Author(s):  
Kléber Luna Altamirano ◽  
Jaime Tinto Arandes ◽  
William Sarmiento Espinoza ◽  
Diego Cisneros Quintanilla

Uno de los problemas más graves que atraviesan las microempresas y empresas en nuestro país, es el referido al problema de los impagos en gestión de tesorería. Este artículo aborda las distintas acciones encaminadas al recobro de un impago mediante la utilización de teoría del expertizaje para alimentar una matriz de efectos olvidados que permita tomar decisiones  y sirva como  instrumento de diseño para representar la política de gestión de cada empresa en las distintas acciones a tomar, es el caso de estudio de los artesanos de calzado del cantón Gualaceo Provincial del Azuay, donde no existe una política adecuada de gestión empresarial para el recobro de impagos por parte de clientes de sus productos. Se indicará paso a paso un grafo representativo de estas políticas a ejecutar en los pagos atrasados por parte de clientes u otras organizaciones con la empresa de calzado, justificando cada arco mediante el uso del análisis de redes neuronales. Una vez conocido la existencia de los impagos se aplica el expertizaje para construir la matriz de convolución que permite descubrir las acciones que han sido olvidadas y que deberá atacar la gerencia para poder tener éxito en la recuperación de los recobros no procesados.Palabras clave: Calzado, expertizaje, impagos, lógica difusa, redes neuronales.  ABSTRACTOne of the most serious problems that the micro companies and companies cross in our country, is recounted to the problem of the non-payments in financiering. This article tackles the different actions directed to the recovery of a non-payment by means of the use of theory of the expertizaje to feed a counterfoil of forgotten effects that allows to take decisions and serves like design instrument to represent the politics of management of every company in the different actions to take, it is the case of study of the craftsmen of footwear of the canton Gualaceo Provincial of the Azuay, where a suitable politics of managerial management does not exist for the non-payments recovery on the part of clients of its products. A graph representative of this politics will be indicated step by step to execute in the payments slowed down on the part of clients or other organizations with the company of footwear, justifying every arch by means of the use of the neural network analysis. Once known the existence of the non-payments applies the expertizaje to itself to construct the counterfoil of convolución that allows to discover the actions that have been forgotten and that the management will have to attack to be able to be successful in the recovery of the not processed recoveries.Keywords: Footwear, expertizaje, non-payments, diffuse logic, neural networks.


2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  

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