In this paper, block distance matrices are introduced. Suppose F is a square block matrix in which each block is a symmetric matrix of some given order. If F is positive semidefinite, the block distance matrix D is defined as a matrix whose (i, j)-block is given by Dij = Fii+Fjj−2Fij . When each block in F is 1 × 1 (i.e., a real number), D is a usual Euclidean distance matrix. Many interesting ...

Recently, several experimental studies have been conducted on block data layout as a data transformation technique used in conjunction with tiling to improve cache performance. In this paper, we provide a theoretical analysis for the TLB and cache performance of block data layout. For standard matrix access patterns, we derive an asymptotic lower bound on the number of TLB misses for any data l...

We develop a Cauchy matrix reduction technique that enables us to obtain solutions for the reduced local and nonlocal complex equations from of original nonreduced systems. Specifically, by imposing reductions on some Ablowitz–Kaup–Newell–Segur-type equations, we study involving modified Korteweg–de Vries equation, sine-Gordon potential nonlinear Schrödinger equation. matrix-type soliton Jordan...

We present a new method for storing sparse matrices as a block matrix-graph where the blocks are stored via a compact, row-ordered scheme. This combines the exibility of the graph structure with the high eeciency of the compact storage technique. The inner compact pattern also allows identiication of entries, which often leads to advantages with respect to memory and computing time. Using this ...

Face is a multidimensional intricate structure that demands good computing technique for recalling it. This paper proposes a new diagonally assisted face recognition technique using Discrete Cosine Transform (DCT). Proposed work divides an image into matrix to apply DCT. Working scheme i.e. DA-DCT selects diagonal coefficient to retain low, moderate and high frequency coefficients for each bloc...

Subspace clustering is a useful technique for many computer vision applications in which the intrinsic dimension of high-dimensional data is often smaller than the ambient dimension. Spectral clustering, as one of the main approaches to subspace clustering, often takes on a sparse representation or a low-rank representation to learn a block diagonal self-representation matrix for subspace gener...

The steganography is an art and science of hiding information into a given media to ensurethe security of information over the communication channel. In this paper we propose a Image Steganography using Average Technique in Transform Domain (ISATT). The Lifting Wavelet Transform (LWT) is applied on both cover image and payload. The Diagonal band (CD) of cover image and Approximation band (PA) o...