We derive an algorithm of optimal complexity which determines whether a given matrix is a Cauchy matrix, and which exactly recovers the Cauchy points defining a Cauchy matrix from the matrix entries. Moreover, we study how to approximate a given matrix by a Cauchy matrix with a particular focus on the recovery of Cauchy points from noisy data. We derive an approximation algorithm of optimal com...

agricultural activities are risky activities. in these activities, various natural, social and economic risks have created fragile and vulnerable situation for producers. price risk in agricultural products has caused financial problems for many producers and farmers. to deal with these price risks and price fluctuations, there are varieties of tools. this paper focused on futures markets instr...

In this paper, we consider the amplified-and-forward relaying in an OFDM system with unitary linear processing at the relay. We proposed a general analytical framework to find the unitary linear processing matrix that maximizes the system achievable rate. We show that the optimal processing matrix is a permutation matrix, which implies that a subcarrier pairing strategy is optimal. We further d...

Kernel methods have been applied successfully in many applications. The kernel matrix plays an important role in kernel-based learning methods, but the “ideal” kernel matrix is usually unknown in practice and needs to be estimated. In this paper, we propose to directly learn the “ideal” kernel matrix (called the optimal neighborhood kernel matrix) from a pre-specified kernel matrix for improved...

in this paper, in order to optimize the portfolio consisting of selected industrial stocks of petroleum products, automobiles and parts, electrical industry and extraction of minerals from tehran stock exchange member, first, time – varying conditional covariance matrix has been estimated based on the following multivariate garch models: diagonal-vech (1,1), ccc (1,1) and diagonal -bekk (1,1). ...

this paper describes an optimal design for multivariable pi controller with a high gain structure for an irregular system by genetic algorithm. pi controllers with a high gain structure leads to the asymptotic decomposition of the fast and slow modes in the closed loop system that have unique characteristics. the slow modes are asymptotically uncontrollable and unobservable; therefore, they hav...

Graph based dimensionality reduction techniques have been successfully applied to clustering and classification tasks. The fundamental basis of these algorithms is the constructed graph which dominates their performance. Usually, the graph is defined by the input affinity matrix. However, the affinity matrix is sub-optimal for dimension reduction as there is much noise in the data. To address t...