𝔖 Bobbio Scriptorium
✦   LIBER   ✦

The Computational Power of ℳω

✍ Scribed by Dag Normann; Christian Rørdam

Publisher
John Wiley and Sons
Year
2002
Tongue
English
Weight
164 KB
Volume
48
Category
Article
ISSN
0044-3050

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

On the computational power of pushdown a
On the computational power of pushdown automata
✍ A.V. Aho; J.D. Ullman; J.E. Hopcroft 📂 Article 📅 1970 🏛 Elsevier Science 🌐 English ⚖ 361 KB

We present a relation between the sets accepted by two-way pushdown automata and certain tape complexity classes of off-line Turing machines. Specifically, let L be a language accepted by a nondeterministic off-line Turing machine T. Let T have a t-symbol storage-tape alphabet. If for all but a fini

Applications of power series in computat
Applications of power series in computational geometry
✍ Yves de Montaudouin; Wayne Tiller; Havard Vold 📂 Article 📅 1986 🏛 Elsevier Science 🌐 English ⚖ 827 KB

A number ofalgortthms are presented for obtaining power series expansions of curves and surfaces at a point. Some results on the radius of convergence are given. Two applications of series are given: • for curve tracing algorithms, where a truncated series ts used to approximate the curve of Inters

On limits on the computational power of
On limits on the computational power of data-accumulating algorithms
✍ Stefan D Bruda; Selim G Akl 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 102 KB

In the data-accumulating paradigm, inputs arrive continuously in real time, and the computation terminates when all the already received data are processed before another datum arrives. Previous research states that a constant upper bound on the running time of a successful algorithm within this par

Computation of powers of multivariate po
Computation of powers of multivariate polynomialsover the integers
✍ Lee E. Heindel 📂 Article 📅 1972 🏛 Elsevier Science 🌐 English ⚖ 328 KB

Theoretical computing time analyses of both the iterative multiplication and binary expansion algorithms for computing pn for P E I [xt ,..., xr] show the iterative multiplication algorithm to be more efficient as r, the number of variables, increases.