The statistical patterns of language are systematic linguistic data which must be accounted for in linguistic theory. The phonotactics of the Arabic verbal roots are presented as a case study. In Arabic, the acceptability of a verbal root is gradiently dependent on the similarity of homorganic consonant pairs within the root. We propose the stochastic constraint model of phonological patterning...

We develop a new modeling and exact solution method for stochastic programming problems that include a joint probabilistic constraint in which the multirow random technology matrix is discretely distributed. We binarize the probability distribution of the random variables in such a way that we can extract a threshold partially defined Boolean function (pdBf) representing the probabilistic const...

In this article, we study and compare two approaches to solving stochastic optimal control problems with an expectation constraint on the final state. The case of a probability constraint is included in this framework. The first approach is based on a dynamic programming principle and the second one uses Lagrange relaxation. These approaches can be used for continuous-time problems; we provide ...

We propose a sample average approximation (SAA) method for stochastic programming problems involving an expected value constraint. Such problems arise, for example, in portfolio selection with constraints on conditional value-at-risk (CVaR). Our contributions include an analysis of the convergence rate and a statistical validation scheme for the proposed SAA method. Computational results using ...

The Wiener-Khintchine theorem dictates that the correlation function of any stationary, stochastic signal y(t) has as its Fourier transform a function that is necessarily both real and non-negative. In this paper, I explore the real-space, geometric consequences of this reciprocal-space non-negativity constraint. I review prior results addressing this issue, and I also introduce a family of new...

Dynamic constraint satisfaction is a useful tool for representing and solving sequential decision problems with complete knowledge in dynamic world. We propose an extension of the dynamic constraint satisfaction framework so as to represent stochastic events in sequential decision making. The basis of this extension consists in modeling evolution of the dynamic constraint satisfaction problem b...

The development of watermarking schemes in the literature is generally guided by a power constraint on the watermark to be embedded into the host. In a steganographic framework there is an additional constraint on the embedding procedure. It states that, for a scheme to be undetectable by statistical means, the pdf of the host signal must be approximately or exactly equal to that of the stegote...

due to the probabilistic nature and uncertainties of structural parameters, reliability-based optimization will enable engineers to account for the safety of the structures and allow for its decision making applicability. thus, reliability-based design will substitute deterministic rules of codes of practice. space structures are of those types that have an exceedingly high range of applicabili...

Continuous constraint reasoning assumes the uncertainty of numerical variables within given bounds and propagates such knowledge through a network of constraints, reducing the uncertainty. In some problems there is also information about the plausibility distribution of values within such bounds. However, the classical constraint framework cannot accommodate that information. This paper describ...

We introduce INDSET, a technique for decomposing a Constraint Satisfaction Problem (CSP) by identifying a maximal independent set in the constraint graph of the CSP. We argue that this technique reduces the complexity of solving the CSP exponentially by the size of the maximal independent set, and yields compact and robust solutions. We discuss how to integrate this decomposition technique with...