The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Structural-parametric synthesis of different types of astatic control systems for electric drives has been implemented with modal control methods. The study has some distinctive features. The first one is the use of dual circuit designs of electromechanical systems with a “rapid” internal control loop. The second one is application of separating a disturbance model into integral and oscillatory components...
The use of computer simulators in modern education is justified for the primary to higher school. The indispensable parts of such simulators are various devices the behavior of which has a dynamic character. Therefore, to create the most adequate computer simulator, it is necessary to develop scientific bases of virtual analogs designed of such objects and combined with the simulation methodology...
Digital predistortion (DPD) is an effective way of mitigating spurious emission violations without the need of a significant backoff in the transmitter, thus providing better power efficiency and network coverage. In this paper, the IM3 subband DPD, proposed earlier by the authors, is extended to more than two component carriers (CCs) through a sequential learning solution. The DPD learning is iterated...
Three methods for extracting the behavioral modeling coefficients of the memory polynomial model are compared herein. The first one is the ordinary least square regression, which is widely used for adjusting model parameters; the second is the order recursive least squares, which is suitable for exploring the optimal nonlinearity order and memory depth by comparing subsequent errors while increasing...
The paper examines the features of IT-projects and their impact on the management decisions of outsourcing companies in their implementation, as well as demonstrates the necessity to apply simulation models of portfolio management of IT-projects. It introduces a system-dynamic model of IT-project with elements of the cognitive approach as a basis for model management of an outsourcing IT-company as...
This paper investigates a cellular edge caching design under an extremely large number of small base stations (SBSs) and users. In this ultra-dense edge caching network (UDCN), SBS-user distances shrink, and each user can request a cached content from multiple SBSs. Unfortunately, the complexity of existing caching controls' mechanisms increases with the number of SBSs, making them inapphcable for...
Indirect measurements of physical parameters of interest often require a mathematical model in which these parameters are estimated accordingly to the gathered measurements. Within the Least Squares estimation, the parameters are estimated through a regression problem. The presence of dynamics, multiple sensors and high sampling rates lead to high dimensional regression matrices. This paper deals...
Many real situations require to find a point to point shortest path having special properties, matching non standard requirements and fulfilling unusual conditions and constraints. It is hard to write a mathematical model for just mentioned problems. One way how to solve this task is to enumerate certain number of shortest paths and to choose from them the most convenient one. There are several k-shortest...
The paper present new method for determination complexity of using in new hyper-hybrid AD HOC cloud computing. A large body of research has been devoted to identifying the complexity of structures in networks. The study of complex networks is a young and active area of scientific research inspired largely by the empirical study of real-world networks such as computer networks and social networks....
Neural networks are a powerful function approximation tool which has the ability to model any function with arbitrary precision. For any function as a black box, it is able to reconstruct the function given the target and the input data. However, there are problems where the target is at least partially unknown. In such cases it is impossible for a traditional neural network to compute the gradient...
Whereas a large number of machine learning methods focus on offline learning over a single batch of data called training data set, the increasing number of automatically generated data leads to the emergence of new issues that offline learning cannot cope with. Incremental learning designates online learning of a model from streaming data. In non-stationary environments, the process generating these...
Although supervisor simplification in the framework of automated manufacturing systems has been studied in many literatures, there is still an intense demand for essential and general techniques. Basically, supervisors can be synthesized by specifications which are expressed by generalized mutual exclusion constraints (GMECs). In this paper, we propose static and dynamic partitions on GMECs to remove...
Hydro-turbine maintenance would be made easier by measuring the multi-scale entropy of its sound and the magnetic waves produced. Currently used methods include parametric solid modeling, FEA analysis, CFD simulation, CAD design & drafting, PLC & SCADA programming, protections, engineering & testing, and power quality testing, among others. The purpose of this paper is to explore specific...
Innovation is neither predictable nor guaranteed within a solution development project. Novel ideas can appear during any level of work, whether high-level design or in code algorithms. As design innovation is a creative action, this paper proposes a vision of related practices, processes and modeling ideas that enable innovation to potentially happen. The practices are mostly mental techniques for...
Let h: ℤ+ → ℤ+ \ {1} be such that (1) h(n) ≤ lg n for all sufficiently large n and (2) h(n) and ⌈n1/h(n)⌉ are computable from n in O(h(n) · n1+1/h(n)) time. We show that given an n-point metric space (M,d), the problem of finding argmini∈M Σj∈Md(i,j) (breaking ties arbitrarily) has a deterministic, O(h(n) · n1+1/h(n))-time, O(n1+1/h(n))-query, (2h(n))-approximation and nonadaptive algorithm. Our derivations...
An expert system (ES) is a computer system that emulates the decision-making ability of a human expert. And it is designed to solve complex problems by reasoning about knowledge, represented primarily as IF-THEN rules. However, the control accuracy is determined by the complexity of the IF-THEN rules, which are designed according to the practical operating experiences. The higher the control accuracy,...
Inference and learning for probabilistic generative networks is often very challenging and typically prevents scalability to as large networks as used for deep discriminative approaches. To obtain efficiently trainable, large-scale and well performing generative networks for semi-supervised learning, we here combine two recent developments: a neural network reformulation of hierarchical Poisson mixtures...
As the successor of H.264, High Efficient Video Coding (HEVC) standard includes various novel techniques, including Coding Tree Unit (CTU) structure and additional angular modes used in intra coding. These new techniques promote the coding efficiency on one hand, while increasing the computational complexity significantly on the other hand. In this paper, we propose a fast intra block partitioning...
The paper deals with realizations of transfer learning for classification, i. e. the adaptation of a classifier model to a changed data distribution. This change could be a data drift or a more complex transformation. We propose to model those data changes by manifolds describing continuous transformations of the data. This description can be seen as a generalization of function based transfer models...
This paper implements an algorithm for constructing Voronoi regions using the method we call "hollow sphere". This principle uses the circle, sphere or hyper-sphere as a geometric structure taking into account an Euclidean space of an arbitrary dimension. Boris Deloné used the property of the empty circle to build the Delaunay triangulation; in our case, the same property is used to perform...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.