Ordered modified Gram-Schmidt orthogonalization revised

FPGA-based Normalization for Modified Gram-Schmidt Orthogonalization

Eigen values evaluation is an integral but computation-intensive part for many image and signal processing applications. Modified Gram-Schmidt Orthogonalization (MGSO) is an efficient method for evaluating the Eigen values in face recognition algorithms. MGSO applies normalization of vectors in its iterative orthogonal process and its accuracy depends on the accuracy of normalization. Using sof...

Experiments on Gram-schmidt Orthogonalization

(3) In addition to solutions for | k | ^ 9999, we have solutions, for y ^ 104 and | k | g 99999; there are 1221 for positive k and 799 for negative k. The vast majority of solutions are with y < 100 and Table 2 gives the number of solutions for various ranges of y. The fact that the number of solutions is a rapidly decreasing function of y suggests that for at least some k the solution set may ...

Gram – Schmidt Orthogonalization on Encrypted Vectors

In this paper we address a privacy preserving version of the well known Gram – Schmidt Orthogonalization procedure. Specifically, we propose a building block for secure multiparty computation, that is able to orthogonalize a set of componentwise encrypted vectors. Our setting is the following: Bob needs to compute this orthogonalization on some vectors encrypted with the public key of Alice. He...

Multiple Description Quantization via Gram-Schmidt Orthogonalization

The multiple description (MD) problem has received considerable attention as a model of information transmission over unreliable channels. A general framework for designing efficient multiple description quantization schemes is proposed in this paper. We provide a systematic treatment of the El Gamal-Cover (EGC) achievable MD rate-distortion region, and show that any point in the EGC region can...

Gram-Schmidt orthogonalization: 100 years and more