Jawad A. K. Hasan

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Principal singular component analysis has recently been proposed and analyzed by the author. It is a generalization of the principal singular subspace analysis which has been investigated in the literature. In this paper an unconstrained weighted cost function is utilized to develop dynamical systems that converge to the actual principal singular vectors of(More)
The ability of brassinosteroids, such as 24-epibrassinolide (EBL) to increase the resistance of oilseed rape plants (Brassica napus L.) to salt stress (175 mM NaCl) was investigated along with the possible mechanisms of their protective action. Seedlings were grown for three weeks on the Hoagland-Snyder medium under controlled conditions. The experimental(More)
The derivation and implementation of many algorithms in sig-nal/image processing and control involve some form of polynomial root-finding and/or matrix eigendecomposition. In this paper, higher order fixed point functions in rational and/or radical forms are developed. This set of iterations can be considered as extensions of known methods such as Newton's,(More)
In this paper, several dynamical systems for computing canon-ical correlations and canonical variates are proposed. These systems are shown to converge to the actual components rather than to a subspace spanned by these components. Using Li-apunov stability theory, qualitative properties of the proposed systems are analyzed in detail including the limit of(More)
Previously, measurement of microbial Adenosine Triphosphate (ATP) has been applied to enumerating bacterial populations in water, wastewater, marine environments, urine, milk, and various foods, just to name a few. However, two universal difficulties were encountered in the application of this method: (1) Interference by non-microbial sources of ATP, and(More)
In thas paper, we have developed an appronch for fzp-proximating the signal and noise suhspnws which avoid the costly eigendecomposataon or SVD. Th~sc subspac~s were approximated using ratzonal and power-lake methods applied to the sample covariance matrix. It 2s shown that MUSIC nnrl Minirnulrr Norm frequency es-timators can he derived using these(More)
Fast algorithms based on the matrix sign function are developed to estimate the signal and noise subspaces of the sample correlation matrices. These subspaces are then utilized to develop high resolution methods such as MUSIC and ESPRIT for sinusoidal frequency and direction of arrival DOA problems. The main feature of these algorithms is that they generate(More)
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