It is shown that a frame of N time slots can be arbitrarily permuted with 2log/sub 2/N-1 controlled exchange switches with associated delay elements. This is an improvement over previously known interconnection networ...
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It is shown that a frame of N time slots can be arbitrarily permuted with 2log/sub 2/N-1 controlled exchange switches with associated delay elements. This is an improvement over previously known interconnection networks that require O(N) exchange elements. The proof utilizes the recursive algorithm of V.E. Benes (1965) and the time interchange properties of a particular configuration of a single exchange element. The architecture is especially applicable in optical systems, since optical exchange switches are among the simplest optical logic devices to build, are inherently very fast, and are the best developed, although expensive.
Efficient algorithms are derived for computing the entries of the Bezout resultant matrix for two univariate polynomials of degree n and for calculating the entries of the Dixon-Cayley resultant matrix for three bivar...
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Efficient algorithms are derived for computing the entries of the Bezout resultant matrix for two univariate polynomials of degree n and for calculating the entries of the Dixon-Cayley resultant matrix for three bivariate polynomials of bidegree (m, n). Standard methods based on explicit formulas require O(n(3)) additions and multiplications to compute all the entries of the Bezout resultant matrix. Here we present a new recursive algorithm for computing these entries that uses only O(n(2)) additions and multiplications. The improvement is even more dramatic in the bivariate setting. Established techniques based on explicit formulas require O(m(4)n(4)) additions and multiplications to calculate all the entries of the Dixon-Cayley resultant matrix. In contrast, our recursive algorithm for computing these entries uses only O(m(2)n(3)) additions and multiplications. (C) 2002 Academic Press.
Let Un denote the number of partitions of the natural number n, all of whose parts bi to {P-n,}- In this note, we present a recursive algorithm for computing Un. The techn used here are also applicable to other second...
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Let Un denote the number of partitions of the natural number n, all of whose parts bi to {P-n,}- In this note, we present a recursive algorithm for computing Un. The techn used here are also applicable to other second order linear recurrences that have the pro] of being super-increasing, that is, where each term exceeds the sum of all its predecessoi [1], the second author solved the corresponding problem for the Fibonacci sequence.
We consider the implications of streaming data for data analysis and data mining. Streaming data are becoming widely available from a variety of sources. In our case we consider the implications arising from Internet ...
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We consider the implications of streaming data for data analysis and data mining. Streaming data are becoming widely available from a variety of sources. In our case we consider the implications arising from Internet traffic data. By implication, streaming data are unlikely to be time homogeneous so that standard statistical and data mining procedures do not necessarily apply. Because it is essentially impossible to store streaming data, we consider recursive algorithms, algorithms which are adaptive and discount the past and also algorithms that create finite pseudo-samples. We also suggest some evolutionary graphics procedures that are suitable for streaming data. We begin our discussion with a discussion of Internet traffic in order to give the reader some sense of the time and data scale and visual resolution needed for such problems.
作者:
XI, ZMCenter of Theoretical Physics
CCAST (World Laboratory) Institute of Theoretical Physics Academia Sinica - P.O. Box 2735 Beijing China
The recursive algorithm of the normal coordinate expansion of the nonlinear sigma-model of Mukhi is extended. A simple background field expansion for the Wess-Zumino-Witten nonlinear sigma-model is presented. The gene...
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The recursive algorithm of the normal coordinate expansion of the nonlinear sigma-model of Mukhi is extended. A simple background field expansion for the Wess-Zumino-Witten nonlinear sigma-model is presented. The general structure of itsn-th order term in the expansion is explicitly given. It is shown that this expansion is equivalent to the usual background field expansion in the matrix form of the chiral model.
We consider the random fragmentation process introduced by Kolmogorov, where a particle having some mass is broken into pieces and the mass is distributed among the pieces at random in such a way that the proportions ...
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We consider the random fragmentation process introduced by Kolmogorov, where a particle having some mass is broken into pieces and the mass is distributed among the pieces at random in such a way that the proportions of the mass shared among different daughters are specified by some given probability distribution (the dislocation law);this is repeated recursively for all pieces. More precisely, we consider a version where the fragmentation stops when the mass of a fragment is below some given threshold, and we study the associated random tree. Dean and Majumdar found a phase transition for this process: the number of fragmentations is asymptotically normal for some dislocation laws but not for others, depending on the position of roots of a certain characteristic equation. This parallels the behavior of discrete analogues with various random trees that have been studied in computer science. We give rigorous proofs of this phase transition, and add further details. The proof uses the contraction method. We extend some previous results for recursive sequences of random variables to families of random variables with a continuous parameter;we believe that this extension has independent interest.
A class of random recursive sequences (Y-n) with slowly varying variances as arising for parameters of random trees or recursive algorithms X leads after normalizations to degenerate limit equations of the form X =(L)...
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A class of random recursive sequences (Y-n) with slowly varying variances as arising for parameters of random trees or recursive algorithms X leads after normalizations to degenerate limit equations of the form X =(L) X. For nondegenerate limit equations the contraction method is a main tool to establish convergence of the scaled sequence to the "unique" solution of the limit equation. In this paper we develop an extension of the contraction method which allows us to derive limit theorems for parameters of algorithms and data structures with degenerate limit equation. In particular, we establish some new tools and a general convergence scheme, which transfers information on mean and variance into a central limit law (with normal limit). We also obtain a convergence rate result. For the proof we use selfdecomposability properties of the limit normal distribution which allow us to mimic the recursive sequence by an accompanying sequence in normal variables.
作者:
ARAVENA, JLDept of Electr. & Comput. Eng.
Louisiana State Univ. Baton Rouge LA USA Abstract Authors References Cited By Keywords Metrics Similar Download Citation Email Print Request Permissions
A recursive algorithm is presented for computing the discrete Fourier transform (DFT). The algorithm is developed for a moving-window-type processing. The computational structure is fully concurrent and allows a vecto...
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A recursive algorithm is presented for computing the discrete Fourier transform (DFT). The algorithm is developed for a moving-window-type processing. The computational structure is fully concurrent and allows a vectorized updating of the DFT. The total time required for the updating could be as low as that of only one multiplication and two additions, regardless of the number of points. A possible structure for executing the computations is developed, and possible enhancements are analyzed.
作者:
Zanetti, RenatoD'Souza, ChristopherCharles Stark Draper Lab
Vehicle Dynam & Controls 17629 El Camino RealSuite 470 Houston TX 77058 USA NASA
Johnson Space Ctr Houston TX 77058 USA NASA
GN & C Autonomous Flight Syst Branch Aerosci & Flight Mech Div Johnson Space Ctr EG6 Houston TX 77058 USA
One method to account for parameters errors in the Kalman filter is to 'consider' their effect in the so-called Schmidt-Kalman filter. This paper addresses issues that arise when implementing a consider Kalman...
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One method to account for parameters errors in the Kalman filter is to 'consider' their effect in the so-called Schmidt-Kalman filter. This paper addresses issues that arise when implementing a consider Kalman filter as a real-time, recursive algorithm. A favorite implementation of the Kalman filter as an onboard navigation subsystem is the UDU formulation. A new way to implement a UDU Schmidt Kalman filter is proposed. The non-optimality of the recursive Schmidt-Kalman filter is also analyzed, and a modified algorithm is proposed to overcome this limitation.
A new method is presented for quickly getting the ODE (ordinary differential equation) associated with the asymptotic properties of the stochastic approximation $X_{n + 1} = X_n + a_n f(X_n ,\zeta _n )$ (or the proj...
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A new method is presented for quickly getting the ODE (ordinary differential equation) associated with the asymptotic properties of the stochastic approximation $X_{n + 1} = X_n + a_n f(X_n ,\zeta _n )$ (or the projected algorithm for the constrained problem). Either $a_n \to 0$, or $a_n $ can be constant, in which case the analysis is on the sequence obtained when $a \to 0$. The method requires that $\{ X_n ,\zeta _{n - 1} \} $ be Markov with a “Feller” transition function, but little else. The simplest result requires that if $X_n \equiv x$, the corresponding noise process $\{ \zeta _n (x),n \geqq 0\} $ have a unique invariant measure; but the “nonunique” case can also be treated. No mixing condition is required, nor the construction of averaged test functions, and $f(\cdot ,\cdot )$ need not be continuous. A detailed analysis of the way that $\{ \zeta _n \} $ varies with $\{ X_n \} $ is not required. For the class of sequences treated, the conditions seem easier to verify than for other methods. There are extensions to the non-Markov case. Two examples illustrate the power and ease of use of the approach. Aside from the advantages of the method in treating standard problems, it seems to be particularly useful for handling the type of iterative algorithms which arise in adaptive communication theory, where the dynamics are often discontinuous and the “noise” is often state-dependent due to the effects of feedback. If the noise $\{ \zeta _n \} $ is not “state-dependent,” then the Markov assumption can be dropped, and the method is even easier to use.
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