Previous resolution-based approaches to theory-guided induction of logic programs produce hypotheses in the form of a set of resolvents of a theory, where the resolvents represent allowed sequences of resolution steps for the initial theory. There are, however, many characterizations of allowed sequences of resolution steps that cannot be expressed by a set of resolvents. One approach to this p...

In the actuarial literature, several exact and approximative recursive methods have been proposed for calculating the distribution of a sum of mutually independent compound Bernoulli distributed random variables. In this paper, we give an overview of these methods. We compare their performance with the straightforward convolution technique by counting the number of dot operations involved in ea...

This paper develops a recursive method for computing moments of 2D objects described by elliptic Fourier descriptors (EFD). To this end, Green’s theorem is utilized to transform 2D surface integrals into 1D line integrals and EFD description is employed to derive recursions for moments computations. A complexity analysis is provided to demonstrate space and time efficiency of our proposed techn...

Recursive subspace model identification (RSMI) has been developed for a decade. Most of RSMIs are only applied for open loop data. In this paper, we propose a new recursive subspace model identification which can be applied under open loop and closed loop data. The key technique of this derivation of the proposed algorithm is to bring the Vector Auto Regressive with eXogenous input (VARX) model...

We show how monotone interpretations – a termination analysis technique for term rewriting systems – can be used to assess the inherent parallelism of recursive programs manipulating inductive data structures. As a side effect, we show how monotone interpretations specify a parallel execution order, and how our approach extends naturally affine scheduling – a powerful analysis used in paralleli...

We present a new approximation technique for quantum field theory. The standard one-loop result is used as a seed for a recursive formula that gives a sequence of improved Gaussian approximations for the generating functional. In a different setting, the basic idea of this recursive scheme is used in the second part of the paper to substantialy speed up the standard Monte Carlo algorithm. http:...

One kind of the colored noise interference systems is generalized output error model (OEARMA). This paper presents a two-stage recursive least squares algorithm for OEARMA. Aiming at the OEARMA, this paper puts forward a two-stage recursive least squares algorithm. The basic idea of the algorithm is to combinie the auxiliary model identification idea and the decomposition technique to decompose...

Recursive Learning (RL) is a circuit-structure-based method for computing all necessary assignments. Recursive learning technique can be combined with diierent CAD algorithms and techniques in testing, veriication and optimization. In particular, it is used for Automatic test pattern generation(ATPG) which has been applied to many areas of logic synthesis and formal veriication including combin...

We describe a technique for inducing recursive functional programs over algebraic datatypes from few non-recursive and only positive ground example-equations. Induction is data-driven and based on structural regularities between example terms. In our approach, functional programs are represented as constructor term rewriting systems containing recursive rewrite rules. In addition to the example...