A metaheuristic procedure based on the Scatter Search approach is proposed for the non-hierarchical clustering problem under the criterion of minimum Sum-of-Squares Clustering. This algorithm incorporates procedures based on different strategies, such as Local Search, GRASP, Tabu Search or Path Relinking. The aim is to obtain quality solutions with short computation times. A series of computati...

The efficiency of the orthogonal least squares (OLS) method for training approximation networks is examined using the criterion of energy compaction. We show that the selection of basis vectors produced by the procedure is not the most compact when the approximation is performed using a nonorthogonal basis. Hence, the algorithm does not produce the smallest possible networks for a given approxi...

The article shows the sequence of development mathematical expressions technical and economic indicators networks whose voltage is up to 1000 V. In these expressions, methods such as smallest squares, criterion analysis were used. From resulting it possible see which sizes are significantly dependent or on costs incurred for this network processing.

privatization advocates believe that transfer to private sector increases firm’s performance and value, business environment, and therefore economic growth and welfare improves. in this research, by using the 70 accepted firms in the tehran stock exchange for the period of 2005 to 2009, we investigate the effect of firm’s ownership structure on their value by applying generalized method of mome...

A series of metaheuristic algorithms is proposed and analyzed for the non-hierarchical clustering problem under the criterion of minimum Sum-of-Squares Clustering. These algorithms incorporate genetic operators and Local Search and Tabu Search procedures. The aim is to obtain quality solutions with short computation times. A series of computational experiments has been performed. The proposed a...

The problem of assessing the performance of algorithms used for the minimization of an l1-penalized least-squares functional, for a range of penalty parameters, is investigated. A criterion that uses the idea of ‘approximation isochrones’ is introduced. Five different iterative minimization algorithms are tested and compared, as well as two warm-start strategies. Both well-conditioned and ill-c...

We propose a new approach for signal reconstruction from non-uniform samples, without constraints on their locations. We look for a function that belongs to a linear shift-invariant space, andminimizes a variational criterion that is a weighted sum of a least-squares data term and a quadratic term penalizing the lack of smoothness. This leads to a resolutiondependent solution, that can be compu...

We propose a new statistical procedure able in some way to overcome the curse of dimensionality without structural assumptions on the function to estimate. It relies on a least-squares type penalized criterion and a new collection of models built from hyperbolic biorthogonal wavelet bases. We study its properties in a unifying intensity estimation framework, where an oracle-type inequality and ...

Clustering is an unsupervised technique dealing with problems of organizing a collection of patterns into clusters based on similarity. Most clustering algorithms are based on hierarchical and partitional approaches. Algorithms based on an hierarchical approach generate a dendrogram representing the nested grouping of patterns and similarity levels at which groupings change [19]. Partitional cl...

A new low-complexity algorithm for data-aided carrier frequency estimation in digital transmission systems is presented. The algorithm is derived from the least-squares (LS) criterion and achieves an estimation accuracy very close to the theoretical limit, even at signal-to-noise ratios (SNR) as low as 0 dB. In conjunction with an FFT, it provides an estimation range of nearly ±50% of the symbo...