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More Efficient Algorithms for Symbolic Network Analysis: Supernodes and Reduced Loop Analysis

  • Ralf Sommer
  • Dirk Ammermann
  • Eckhard Hennig
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 219)

Abstract

In this paper, two efficient approaches will be discussed that support linear network analysis: supernode analysis (SNA) and reduced loop analysis (RLA). By means of some selected example networks, these methods will be demonstrated and, thus, it will be shown that calculations can be dramatically simplified. In this way, all network situations can be handled. There are obvious advantages to SNA as it combines the MNA and the straightforward manual processing of the network. A very efficient solution strategy is obtained without source shifting and other common, less directed methods being used. SNA/RLA and symbolic algebra fit extremely well together. Thus an algorithm that supports the symbolic calculation of networks by means of supernodes which has been conceptualized and implemented in the analog design expert system EASY will be presented in detail. Above the educational aspect, it should be noted that the computer can now take a systematic approach to MNA and network analysis in general.

Keywords

Current Source Voltage Source Loop Current Forced Condition Element Relation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1993

Authors and Affiliations

  • Ralf Sommer
    • 1
  • Dirk Ammermann
    • 1
  • Eckhard Hennig
    • 1
  1. 1.Institut für Netzwerktheorie und SchaltungstechnikTechnische Universität Braunschweig

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