A new square root state estimation algorithm is introduced, that operates in the information mode in both the time and the measurement update stages. The algorithm, called the V-Lambda filter, is based on the spectral decomposition of the covariance matrix into a V\V form, where V is the matrix whose columns are the eigenvectors of the covariance matrix, and A is the diagonal matrix of its eige...

In this paper, we show that a matrix A in Mn(C) that has n coneigenvectors, where coneigenvaluesassociated with them are distinct, is condiagonalizable. And also show that if allconeigenvalues of conjugate-normal matrix A be real, then it is symmetric.  

Bilinear pooling of Convolutional Neural Network (CNN) features [22, 23], and their compact variants [10], have been shown to be effective at fine-grained recognition, scene categorization, texture recognition, and visual question-answering tasks among others. The resulting representation captures second-order statistics of convolutional features in a translationally invariant manner. In this p...

Matrices with the restricted isometry property (RIP) are of particular interest in compressed sensing. To date, the best known RIP matrices are constructed using random processes, while explicit constructions are notorious for performing at the “square-root bottleneck,” i.e., they only accept sparsity levels on the order of the square root of the number of measurements. The only known explicit ...

In this paper we propose design of three systolic arrays to perform QR decomposition of a square matrix. Our first design is based on Given’s rotation method [1]. In contrast to the earlier designs [1], [2] based on this method, our design uses n(n − 1)/2 homogeneous PEs. Our next design is based on Householder method [4]. This method performs only (n− 1) square root operations in contrast to n...