An efficient parallel implementation of a least squares problem

Least squares solutions are a very important problem, which appear in a broad range of disciplines (for instance, control systems, statistics, signal processing). Our interest in this kind of problems lies in their use of training neural network controllers.

An efficient parallel implementation of a least squares problem

Least squares solutions are a very important problem, which appear in a broad range of disciplines (for instance, control systems, statistics, signal processing). Our interest in this kind of problems lies in their use of training neural network controllers.

Local object gist: meaningful shapes and spatial layout at a very early stage of visual processing

In his introduction, Pinna (2010) quoted one of Wertheimer’s observations: “I stand at the window and see a house, trees, sky. Theoretically I might say there were 327 brightnesses and nuances of color. Do I have ‘327’? No. I have sky, house, and trees.” This seems quite remarkable, for Max Wertheimer, together with Kurt Koffka and Wolfgang Koehler, was a pioneer of Gestalt Theory: perceptual organisation was tackled considering grouping rules of line and edge elements in relation to figure-ground segregation, i.e., a meaningful object (the figure) as perceived against a complex background (the ground). At the lowest level – line and edge elements – Wertheimer (1923) himself formulated grouping principles on the basis of proximity, good continuation, convexity, symmetry and, often forgotten, past experience of the observer. Rubin (1921) formulated rules for figure-ground segregation using surroundedness, size and orientation, but also convexity and symmetry. Almost a century of research into Gestalt later, Pinna and Reeves (2006) introduced the notion of figurality, meant to represent the integrated set of properties of visual objects, from the principles of grouping and figure-ground to the colour and volume of objects with shading. Pinna, in 2010, went one important step further and studied perceptual meaning, i.e., the interpretation of complex figures on the basis of past experience of the observer. Re-establishing a link to Wertheimer’s rule about past experience, he formulated five propositions, three definitions and seven properties on the basis of observations made on graphically manipulated patterns. For example, he introduced the illusion of meaning by comics-like elements suggesting wind, therefore inducing a learned interpretation. His last figure shows a regular array of squares but with irregular positions on the right side. This pile of (ir)regular squares can be interpreted as the result of an earthquake which destroyed part of an apartment block. This is much more intuitive, direct and economic than describing the complexity of the array of squares.

Local gist vision of man-made objects

Attention is usually modelled by sequential fixation of peaks in saliency maps. Those maps code local conspicuity: complexity, colour and texture. Such features have no relation to entire objects, unless also disparity and optical flow are considered, which often segregate entire objects from their background. Recently we developed a model of local gist vision: which types of objects are about where in a scene. This model addresses man-made objects which are dominated by a small shape repertoire: squares, rectangles, trapeziums, triangles, circles and ellipses. Only exploiting local colour contrast, the model can detect these shapes by a small hierarchy of cell layers devoted to low- and mid-level geometry. The model has been tested successfully on video sequences containing traffic signs and other scenes, and partial occlusions were not problematic.

Adaptive generalized predictive control algorithm implemented over an heterogeneous parallel architecture

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Adaptive generalized predictive control algorithm implemented over a DSP network

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Implementation of an daptive generalized predictive control algorithm over an heterogeneous parallel architecture

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Parallel implementation of an adaptive generalized predictive control algorithm

The Adaptive Generalized Predictive Control (AGPC) algorithm can be speeded up using parallel processing. Since the AGPC algorithm needs to be fed with the knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Parallel implementation of an adaptive generalized predictive control algorithm

The Adaptive Generalized Predictive Control (GPC) algorithm can be speeded up using parallel processing. Since the GPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Parallel implementation of a learning algorithm for multilayer perceptrons using transputers

In this paper the parallelization of a new learning algorithm for multilayer perceptrons, specifically targeted for nonlinear function approximation purposes, is discussed. Each major step of the algorithm is parallelized, a special emphasis being put in the most computationally intensive task, a least-squares solution of linear systems of equations.

Chromatographic analysis and comparison of chemical composition of the samples between olive oils in Europe and some chinese oils

Dissertação de mest., Qualidade em Análises, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2013