An algorithm is developed for the exact simulation from distributions that are deened as xed-points of maps between spaces of probability measures. The xed-points of the class of maps under consideration include examples of limit distributions of random variables studied in the probabilistic analysis of algorithms. The sampling algorithm relies on a modiied rejection method.

The square root function has a unique positive ¿xed point. This function has the following properties: it is strictly increasing and strictly concave, with sEf ' f, sE@ : @ for @ , and sEK K for K : . It is shown that any function from U to U satisfying these properties has a unique positive ¿xed point.

In this paper we underline the importance of the parametric subregularity property of setvalued mappings, de…ned with respect to …xed sets. We show that this property appears naturally for some very simple mappings which play an important role in the theory of metric regularity. We prove a result concerning the preservation of metric subregularity at generalized compositions. Then we obtain, on...

We present global and local algorithms for evaluating minimal xed points of dependency graphs, a general problem in xed-point computation and model checking. Our algorithms run in linear-time, matching the complexity of the best existing algorithms for similar problems, and are simple to understand. The main novelty of our global algorithm is that it does not use the counter and \reverse list" ...

The breakdown point behavior of M-estimators in linear models with xed designs, arising from planned experiments or qualitative factors, is characterized. Particularly, this behavior at xed designs is quite diierent from that at designs which can be corrupted by outliers|the situation prevailing in the literature. For xed designs, the breakdown points of robust M-estimators (those with bounded ...

We apply genetic algorithms to the Hop eld's neural network model of associative memory. Previously, we reported that random synaptic weights of the network evolved to create the xed point attractors exactly at the locations of given patterns. Furthermore, we reported that the genetic algorithm can evolve the Hebbian synaptic weights to enlarge the storage capacity. In those experiments, the ge...

In this correspondence, a stable nite precision Recursive Least Squares (RLS) algorithm is derived for the prewindowed growing memory case (forgetting factor, = 1). Previously, it has been shown that the prewindowed growing memory RLS algorithm diverges under xed-point implementation 1, 2]. The random walk phenomenon due to roundoo errors in the weight update causes the divergence of the algori...

In this paper we extend the technique of computer{assisted proofs to xed point problems in Sobolev spaces. Up to now the method was limited to the case of spaces of analytic functions. The possibility to work with Sobolev spaces is an important progress and opens up many new domains of applications. Our discussion is centered around a concrete problem that arises in the theory of critical pheno...