This communication deals with the problem of state estimation for a class of non linear singular systems. Sufficient conditions for the existence of such observers are provided and the design of an observer is examined. Assuming that the measurement matrix is full row rank involves many calculation simplifications ; therefore special emphasis in the computational aspect of the observer matrices...

Regions in the genome that affect complex traits, quantitative trait loci (QTL), can be identified using statistical analysis of genetic and phenotypic data. When restricted maximum-likelihood (REML) models are used, the mapping procedure is normally computationally demanding. We develop a new efficient computational scheme for QTL mapping using variance component analysis and the AI-REML algor...

Conceptual metaphors are linguistic constructions. Such a metaphor is humans' mental representation of social rank as a pyramidal-like structure. High-ranked individuals are represented in higher positions than low-ranked individuals. We show that conceptual metaphorical mapping between social rank and the representational domain exists in our closest evolutionary relatives, the chimpanzees. Ch...

Annotating remote sensing images is a challenging task for its labor demanding annotation process and requirement of expert knowledge, especially when images can be annotated with multiple semantic concepts (or labels). To automatically annotate these multi-label images, we introduce an approach called Multi-Label Classification based on Low Rank Representation (MLC-LRR). MLC-LRR firstly utiliz...

In this paper we investigate some matrix structures on C that have a good behaviour under Schur complementation. The first type of structure is closely related to low displacement rank matrices. Next, we show that for a matrix having a low rank submatrix, also the Schur complement must have a low rank submatrix, which we can explicitly determine. This property holds even if the low rank submatr...

We propose a method for rank k approximation to a given input matrix X P R which runs in time

Recently, low-rank and sparse model-based dimensionality reduction (DR) methods have aroused lots of interest. In this paper, we propose an effective supervised DR technique named block-diagonal constrained low-rank and sparse-based embedding (BLSE). BLSE has two steps, i.e., block-diagonal constrained low-rank and sparse representation (BLSR) and block-diagonal constrained low-rank and sparse ...

Using the matrix product state (MPS) representation of tensor train decompositions, in this paper we propose a tensor completion algorithm which alternates over the matrices (tensors) in the MPS representation. This development is motivated in part by the success of matrix completion algorithms which alternate over the (low-rank) factors. We comment on the computational complexity of the propos...