This paper considers the design of quadrature mirror lter (QMF) banks whose analysis and synthesis lters are FIR and have linear phase. The design criterion is of least-squares type. An iterative computation algorithm is proposed, and its convergence is proven that ooers new insight to the design of QMF banks, and relates it to a more general nonlinear optimization problem.

This article gives ideas for developing statistics software which can work without user intervention. Some popular methods of bandwidth selection for kernel density estimation (the nearest neighbour, least squares cross-validation, “plug-in” technique) are discussed. Modifications of the cross-validation criterion are proposed. Two-stage estimators combining these methods with multiplicative bi...

The spectrum ?(G) of a finite group G is the set orders its elements. following sufficient criterion nonsolvability proved: if, among prime divisors order G, there are four different primes such that contains all their pairwise products but not product any three these numbers, then nonsolvable. Using this result, we show for q ? 8 and ? 32, direct square Sz(q) × simple exceptional Suzuki unique...

Model-based elastography is fraught with problems owing to the ill-posed nature of the inverse elasticity problem. To overcome this limitation, we have recently developed a novel inversion scheme that incorporates a priori information concerning the mechanical properties of the underlying tissue structures, and the variance incurred during displacement estimation in the modulus image reconstruc...

A synchronization criterion for overlap-add time-scale modification is derived through a least squares estimation of the modified short-time Fourier transform. Based on this finding, a structural time-domain framework for time-scale modification is described. One efficient variant, which was called the Waveform Similarity based Overlap-Add (WSOLA) method, produces high quality output when appli...

Linear discriminant analysis (LDA) for dimension reduction has been applied to a wide variety of problems such as face recognition. However, it has a major computational difficulty when the number of dimensions is greater than the sample size. In this paper, we propose a margin based criterion for linear dimension reduction that addresses the above problem associated with LDA. We establish an e...

Introduction and Summary The use of regression analysis relies on the choice of a criterion in order to estimate the coefficients of the explanatory variables. Traditionally, the least squares (LS) criterion has been the method of choice. However, the least absolute value (LAV) criterion provides an alternative. LAV regression coefficients are chosen to minimize the sum of the absolute values o...

Traditional bidirectional two-dimension (2D) principal component analysis ((2D)PCA-L2) is sensitive to outliers because its objective function is the least squares criterion based on L2-norm. This paper proposes a simple but effective L1-norm-based bidirectional 2D principal component analysis ((2D)PCA-L1), which jointly takes advantage of the merits of bidirectional 2D subspace learning and L1...

Modified (r, k) class ridge regression (MCRR) which includes unbiased ridge regression (URR), (r, k) class, principal components regression (PCR) and the ordinary least squares (OLS) estimators is proposed in regression analysis, to overcome the problem of multicollinearity. In this paper, we derive the necessary and sufficient conditions for the superiority of the MCRR estimator over each of t...