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Dynamic Normal Forms and Dynamic Characteristic Polynomial

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5125))

Abstract

We present the first fully dynamic algorithm for computing the characteristic polynomial of a matrix. In the generic symmetric case our algorithm supports rank-one updates in O(n 2 logn) randomized time and queries in constant time, whereas in the general case the algorithm works in O(n 2 k logn) randomized time, where k is the number of invariant factors of the matrix. The algorithm is based on the first dynamic algorithm for computing normal forms of a matrix such as the Frobenius normal form or the tridiagonal symmetric form. The algorithm can be extended to solve the matrix eigenproblem with relative error 2− b in additional O(n log2 n logb) time. Furthermore, it can be used to dynamically maintain the singular value decomposition (SVD) of a generic matrix. Together with the algorithm the hardness of the problem is studied. For the symmetric case we present an Ω(n 2) lower bound for rank-one updates and an Ω(n) lower bound for element updates.

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Frandsen, G.S., Sankowski, P. (2008). Dynamic Normal Forms and Dynamic Characteristic Polynomial. In: Aceto, L., Damgård, I., Goldberg, L.A., Halldórsson, M.M., Ingólfsdóttir, A., Walukiewicz, I. (eds) Automata, Languages and Programming. ICALP 2008. Lecture Notes in Computer Science, vol 5125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70575-8_36

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  • DOI: https://doi.org/10.1007/978-3-540-70575-8_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70574-1

  • Online ISBN: 978-3-540-70575-8

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