Recently a model for supervised learning of probabilistic transduc ers represented by su x trees was introduced However this algo rithm tends to build very large trees requiring very large amounts of computer memory In this paper we propose a new more com pact transducer model in which one shares the parameters of distri butions associated to contexts yielding similar conditional output distrib...

in this paper, we introduce and study a mixed variational inclusion problem involving infinite family of fuzzy mappings. an iterative algorithm is constructed for solving a mixed variational inclusion problem involving infinite family of fuzzy mappings and the convergence of iterative sequences generated by the proposed algorithm is proved. some illustrative examples are also given.

We present a new type of Markov Chain algo rithm for the calculation of combined Dempster Shafer belief which is almost linear in the size of the frame thus making the calculation of belief feasible for a wider range of problems We also indicate how these algorithms may be used in the cal culation of belief in product spaces associated with networks

In this paper an algorithm for the calculation of the root locus of fractional linear systems is presented. The proposed algo rithm takes advantage of present day computational resources and processes directly the characteristic equation, avoiding the limitations revealed by standard methods. The results demonstrate the good performance for different types of expressions.

We give geometrical conditions, which guarantee the existence of a diffeomorphism in order to transform a nonlinear system without inputs into a canonical normal form depending on its output. Moreover we extend our results to a class of systems with inputs. We end this paper by some examples and its simulations to highlight the proposed algo rithm.

Presented here is a generalization of the implicit enumeration algorithm that can be applied when the objec-tive function is being maximized and can be rewritten as the difference of two non-decreasing functions. Also developed is a computational algorithm, named linear speedup, to use whatever explicit linear constraints are present to speedup the search for a solution. The method is easy to u...

We present a novel EM algorithm for model-based image segmentation which incorporates efficient and economical spatial constrains among pixels via a Markov random field model. We adopt a generative model in which the unobserved class labels of neighboring pixels in the image are assumed to be generated by prior distributions with similar parameters. We derive a penalized log-likelihood optimiza...

This paper presents a fast and effective electromagnetic reconstruction algorithm with phaseless data under weak scattering conditions. The proposed algorithm is based on the phaseless data multiplicative regularized contrast sources inversion method (PDMRCSI). We recast the weak scattering problem as an optimization problem in terms of the undetermined contrast and contrast sources. Using the ...

Given a set of n points and hyperrectangles in d dimensional space the batched range searching problem is to determine which points each hyperrectangle contains We present two parallel algorithms for this problem on a p n pn mesh connected paral lel computer one average case e cient algorithm based on cell division and one worst case e cient divide and conquer algo rithm Besides the asymptotic ...

Location estimation of mobile phones has received considerable interest in the eld of wireless communications In this pa per a simple and e cient positioning algo rithm using received signal strength measure ments obtained from at least three base stations are developed Our proposed method is based on solving a nonconvex constrained weighted least squares problem Simulation results show that th...