We consider Fair Principal Component Analysis (FPCA) and search for a low dimensional subspace that spans multiple target vectors in fair manner. FPCA is defined as non-concave maximization of the worst projected norm within given set. The problem arises filter design signal processing, when incorporating fairness into dimensionality reduction schemes. state art approach to via semidefinite rel...

z In this paper, the one-dimensional principal component lter banks (PCFB's) derived in 17] are generalized to higher dimensions. As presented in 17], PCFB's minimize the mean-squared error (MSE) when only Q out of P subbands are retained. Previously, 2D PCFB's were proposed in 16]. The work in 16] was limited to 2D signals and separable resampling operators. The formulation presented here is g...

Figure 1. Spectral filtering of Habronattus pyrrithrix photoreceptors. (A) Courtship display of male H. pyrrithrix (photo: Colin Hutton). (B) Boomerang-shaped retinas superimposed on principal eye lenses, small red area indicates filter position. (C) Red filter pigment visible in unstained coronal cryosection (14 μm thick) of the principal retina. (D) Tiered retina structure in thin horizontal ...

The purpose of this paper is to demonstrate the optimality properties of principal component filter-banks for various noise reduction schemes. Optimization of filter-banks (FB’s) for coding gain maximization has been carried out in the literature, and the optimized solutions have been observed to satisfy the principal component property, which has independently been studied. Here we show a stro...

Aerosol filtration in fibrous filters is one of the principal methods of removal of solid particles from the gas stream. The classical theory of depth filtration is based on the assumption of existing single fiber efficiency, which may be used to the recalculation of the overall efficiency of the entire filter. There are several reasons for inappropriate estimation of the single fi...

In this paper we develop a method to optimize a machine-based semantic categorization of natural images according to human perception. First, the categories are determined through a psychophysical experiment. The similarity matrices obtained from human responses are analyzed by a multidimensional scaling technique called Curvilinear Component Analysis (CCA). The same is done with an automatic i...