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Identification (information)

About: Identification (information) is a(n) research topic. Over the lifetime, 52767 publication(s) have been published within this topic receiving 587580 citation(s). The topic is also known as: notset & identify. more


Journal ArticleDOI: 10.1109/72.80202
Abstract: It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems. The emphasis is on models for both identification and control. Static and dynamic backpropagation methods for the adjustment of parameters are discussed. In the models that are introduced, multilayer and recurrent networks are interconnected in novel configurations, and hence there is a real need to study them in a unified fashion. Simulation results reveal that the identification and adaptive control schemes suggested are practically feasible. Basic concepts and definitions are introduced throughout, and theoretical questions that have to be addressed are also described. > more

Topics: Nonlinear system identification (59%), Adaptive control (57%), Dynamical systems theory (56%) more

7,508 Citations

Open accessBook
01 Jan 1983-
Abstract: Methods of recursive identification deal with the problem of building mathematical models of signals and systems on-line, at the same time as data is being collected. Such methods, which are also k ... more

2,959 Citations

Open accessJournal Article
Abstract: Identification of information needs of top management is discussed in this article by comparing four methods now in use with a new approach, "identification of critical success factors," developed at the Sloan School of Management. The author argues that the CSF method, implemented through a series of two to three interview sessions, helps top management define its own current information needs. Critical success factors are those performance factors which must receive the on-going attention of management if the company is to remain competitive. While not intended for strategic planning purposes, the identification of critical success factors can help top management by: (1) determining where management attention should be directed; (2) developing measures for critical success factors; and (3) determining the amount of information required and thus limiting gathering unnecessary data. The author concludes that the CSF method is both effective and efficient and should be seriously considered by top management as an important tool in assessing data needs. more

Topics: Critical success factor (64%), Information needs (58%), Information system (55%) more

2,810 Citations

Open accessJournal ArticleDOI: 10.1103/PHYSREVE.76.036106
11 Sep 2007-Physical Review E
Abstract: Community detection and analysis is an important methodology for understanding the organization of various real-world networks and has applications in problems as diverse as consensus formation in social communities or the identification of functional modules in biochemical networks. Currently used algorithms that identify the community structures in large-scale real-world networks require a priori information such as the number and sizes of communities or are computationally expensive. In this paper we investigate a simple label propagation algorithm that uses the network structure alone as its guide and requires neither optimization of a predefined objective function nor prior information about the communities. In our algorithm every node is initialized with a unique label and at every step each node adopts the label that most of its neighbors currently have. In this iterative process densely connected groups of nodes form a consensus on a unique label to form communities. We validate the algorithm by applying it to networks whose community structures are known. We also demonstrate that the algorithm takes an almost linear time and hence it is computationally less expensive than what was possible so far. more

Topics: Clique percolation method (59%), Node (networking) (53%), Time complexity (51%) more

2,673 Citations

Journal ArticleDOI: 10.1016/0165-0114(88)90113-3
Michio Sugeno1, G. T. Kang1Institutions (1)
Abstract: The problems of structure identification of a fuzzy model are formulated. A criterion for the verification of a structure is discussed. Using the criterion, an algorithm for identifying a structure is suggested. Further, a successive identification algorithm of the parameters is suggested. The proposed methods are applied to an example. more

2,548 Citations

No. of papers in the topic in previous years

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Topic's top 5 most impactful authors

Lennart Ljung

59 papers, 5.8K citations

Michel Verhaegen

15 papers, 430 citations

Arne Dankers

11 papers, 141 citations

Ichiro Futamura

8 papers, 392 citations

Sviatoslav Voloshynovskiy

8 papers, 153 citations

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