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Progress in Inverse Spectral Geometry (Hardcover, 1997 ed.): Stig I. Andersson, Michel L Lapidus Progress in Inverse Spectral Geometry (Hardcover, 1997 ed.)
Stig I. Andersson, Michel L Lapidus
R4,030 R1,653 Discovery Miles 16 530 Save R2,377 (59%) Ships in 12 - 17 working days

most polynomial growth on every half-space Re (z)::::: c. Moreover, Op(t) depends holomorphically on t for Re t > O. General references for much of the material on the derivation of spectral functions, asymptotic expansions and analytic properties of spectral functions are A-P-S] and Sh], especially Chapter 2. To study the spectral functions and their relation to the geometry and topology of X, one could, for example, take the natural associated parabolic problem as a starting point. That is, consider the 'heat equation' (%t + p) u(x, t) = 0 { u(x, O) = Uo(x), tP which is solved by means of the (heat) semi group V(t) = e-; namely, u(., t) = V(t)uoU. Assuming that V(t) is of trace class (which is guaranteed, for instance, if P has a positive principal symbol), it has a Schwartz kernel K E COO(X x X x Rt, E* (r)E), locally given by 00 K(x, y; t) = L>-IAk( k (r) 'Pk)(X, y), k=O for a complete set of orthonormal eigensections 'Pk E COO(E). Taking the trace, we then obtain: 00 tA Op(t) = trace(V(t)) = 2:: >- k. k=O Now, using, e. g., the Dunford calculus formula (where C is a suitable curve around a(P)) as a starting point and the standard for malism of pseudodifferential operators, one easily derives asymptotic expansions for the spectral functions, in this case for Op."

Progress in Inverse Spectral Geometry (Paperback, Softcover reprint of the original 1st ed. 1997): Stig I. Andersson, Michel L... Progress in Inverse Spectral Geometry (Paperback, Softcover reprint of the original 1st ed. 1997)
Stig I. Andersson, Michel L Lapidus
R1,515 Discovery Miles 15 150 Ships in 10 - 15 working days

most polynomial growth on every half-space Re (z)::::: c. Moreover, Op(t) depends holomorphically on t for Re t > O. General references for much of the material on the derivation of spectral functions, asymptotic expansions and analytic properties of spectral functions are A-P-S] and Sh], especially Chapter 2. To study the spectral functions and their relation to the geometry and topology of X, one could, for example, take the natural associated parabolic problem as a starting point. That is, consider the 'heat equation' (%t + p) u(x, t) = 0 { u(x, O) = Uo(x), tP which is solved by means of the (heat) semi group V(t) = e-; namely, u(., t) = V(t)uoU. Assuming that V(t) is of trace class (which is guaranteed, for instance, if P has a positive principal symbol), it has a Schwartz kernel K E COO(X x X x Rt, E* (r)E), locally given by 00 K(x, y; t) = L>-IAk( k (r) 'Pk)(X, y), k=O for a complete set of orthonormal eigensections 'Pk E COO(E). Taking the trace, we then obtain: 00 tA Op(t) = trace(V(t)) = 2:: >- k. k=O Now, using, e. g., the Dunford calculus formula (where C is a suitable curve around a(P)) as a starting point and the standard for malism of pseudodifferential operators, one easily derives asymptotic expansions for the spectral functions, in this case for Op."

Analysis of Dynamical and Cognitive Systems - Advanced Course, Stockholm, Sweden, August 9 - 14, 1993. Proceedings (Paperback,... Analysis of Dynamical and Cognitive Systems - Advanced Course, Stockholm, Sweden, August 9 - 14, 1993. Proceedings (Paperback, 1995 ed.)
Stig I. Andersson
R1,621 Discovery Miles 16 210 Ships in 10 - 15 working days

This volume constitutes the documentation of the advanced course on Analysis of Dynamical and Cognitive Systems, held during the Summer University of Southern Stockholm in Stockholm, Sweden in August 1993.
The volume contains eight carefully revised full versions of the invited three-to-four hour presentations as well as two abstracts. As a consequence of the interdisciplinary topic, several aspects of dynamical and cognitive systems are addressed: there are three papers on computability and undecidability, five tutorials on diverse aspects of universal cellular neural networks, and two presentations on dynamical systems and complexity.

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