Ieee Transactions on Neural Networks

نویسندگان

  • Robert Cimikowski
  • Paul Shope
چکیده

|We present a neural network algorithm for minimizing edge crossings in drawings of nonplanar graphs. This is an important subproblem encountered in graph layout. The algorithm nds either the minimum number of crossings or an approximation thereof and also provides a linear embedding realizing the number of crossings found. The parallel time complexity of the algorithm is O(1) for a neural network with n 2 processing elements, where n is the number of vertices of the graph. We present results from testing a sequential simulator of the algorithm on a set of nonplanar graphs and compare its performance with the heuristic of Nicholson.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Editorial: Welcome To The IEEE Neural Networks Society

I WANT towelcomeyou toournewly formedsociety.On February 17, 2002, the IEEE Neural Networks Council (NNC), publisher of the IEEE TRANSACTIONS ON NEURAL NETWORKS (TNN), the IEEE TRANSACTIONS ON FUZZY SYSTEMS (TFS), and the IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (TEC), became the IEEE Neural Networks Society (NNS). This accomplishment was made possible by the relentless efforts of our ExCo...

متن کامل

February 2010 | Ieee Computational Intelligence Magazine 5 Spotlight Publication Publication Publication Cis Publication Spotlight Ieee Transactions on Neural Networks Ieee Transactions on Fuzzy Systems

Digital Object Identifier: 10.1109/ TNN.2009.2025946 “Convergence analysis of the online BP training algorithm was proved using two fundamental theorems: One theorem claims that under mild conditions, the gradient sequence of the error function will converge to zero (the weak convergence), and another theorem concludes the convergence of the weight sequence defined by the procedure to a fixed v...

متن کامل

Using Directional Fibers to Locate Fixed Points of Recurrent Neural Networks.

We introduce mathematical objects that we call ``directional fibers,'' and show how they enable a new strategy for systematically locating fixed points in recurrent neural networks. We analyze this approach mathematically and use computer experiments to show that it consistently locates many fixed points in many networks with arbitrary sizes and unconstrained connection weights. Comparison with...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1996