Proyecto de sistematización de la ética luliana

For classifying multispectral satellite images, a multilayer perceptron (MLP) is trained using either (i) ground truth data or (ii) the output of a K-means clustering program or (iii) both, as applied to certain representative parts of the given data set. In the second case, different sets of clustered image outputs, which have been checked against actual ground truth data wherever available, are used for testing the MLP. The cover classes are, typically, different types of (a) vegetation (including forests and agriculture); (b) soil (including mountains, highways and rocky terrain); and (c) water bodies (including lakes). Since the extent of ground truth may not be sufficient for training neural networks, the proposed procedure (of using clustered output images) is believed to be novel and advantageous. Moreover, it is found that the MLP offers an accuracy of more than 99% when applied to the multispectral satellite images in our library. As importantly, comparison with some recent results shows that the proposed application of the MLP leads to a more accurate and faster classification of multispectral image data

A SOM-based Chan–Vese model for unsupervised image segmentation

Active Contour Models (ACMs) constitute an efficient energy-based image segmentation framework. They usually deal with the segmentation problem as an optimization problem, formulated in terms of a suitable functional, constructed in such a way that its minimum is achieved in correspondence with a contour that is a close approximation of the actual object boundary. However, for existing ACMs, handling images that contain objects characterized by many different intensities still represents a challenge. In this paper, we propose a novel ACM that combines—in a global and unsupervised way—the advantages of the Self-Organizing Map (SOM) within the level set framework of a state-of-the-art unsupervised global ACM, the Chan–Vese (C–V) model. We term our proposed model SOM-based Chan– Vese (SOMCV) active contourmodel. It works by explicitly integrating the global information coming from the weights (prototypes) of the neurons in a trained SOM to help choosing whether to shrink or expand the current contour during the optimization process, which is performed in an iterative way. The proposed model can handle images that contain objects characterized by complex intensity distributions, and is at the same time robust to the additive noise. Experimental results show the high accuracy of the segmentation results obtained by the SOMCV model on several synthetic and real images, when compared to the Chan–Vese model and other image segmentation models

On the Stability of a Linear Time-Varying System

A single-loop linear system with a time-invariant stable blockGin the direct path and a time-varying gain in the feedback path is analyzed for asymptotic stability in the Popov framework by way of admitting noncausal "multipliers" in the stability criterion. It is shown that an auto-correlation bound, analogous to O'Shea's cross-correlation bounds [1], results in a constraint on dk/dt more restrictive than that of Gruber and Willems [2]

Converse hölder inequality and the Lp-instability of nonlinear time-varying feedback systems

WE DEAL with the Lp-instability of a nonlinear time-varying feedback system governed by the pair of equations: v(t) = x(t) - k(t)cp (y(t)),y(t) = (qJv)(t) (1) := ~ g i v ( t - ri) + g( O v ( t - r) dr i=1 for all t I> 0, where x, v, and y are respectively the input to the system, the error signal and output of the system; N is a time-invariant linear operator; qv is a first and third quadrant continuous, memoryless (monotone) nonlinearity; and k is a time-varying gain. For assumptions on the components of (1), see Section 2 below. We derive Lp-instability conditions in terms of the frequency response of ~3 and a general causal + anticausal multiplier function. The derivation is based on the converse H61der inequality and the "energy balance" argument as used in [1].The problem of instability of feedback systems with a single time-varying nonlinearity was initially considered by Brockett and Lee [2] who, in a Lyapunov-Chetaev setting, derived an instability version of the circle criterion [3, 4] under certain assumptions on the related linear time-invariant systemwith a constant gain in the feedback loop. It is found that this instability theorem is conservative [5, Section 5]. See [5] for references to other instability results. As far as the analysis of instability of feedback systems by functional methods is concerned,different types of results are available. Willems [6] extends the domain of operators and imbedsthe system causal operator in a noncausal operator in an attempt to prove the noncausality of the inverse of the original operator by contradiction. This technique has been explicitly used [7] but there do exist certain unresolvable difficulties [8; 9, Chapter 7]. Similar difficulties are encountered in the results of Takeda and Bergen [10, 11] and Steding and Bergen [12], who consider a subclass of inputs over which the linear time-invariant part of the system is well- behaved (and satisfies some additional conditions), and prove instability by contradiction. See [9, Chapter 7] for a complete analysis of these contributions in which, more importantly, the assumptions made on the linear time-invariant part of the system are too severe

An exponential stability criterion for certain nonlinear systems

Improved sufficient conditions are derived for the exponential stability of a nonlinear time varying feedback system having a time invariant blockG in the forward path and a nonlinear time varying gain ϕ(.)k(t) in the feedback path. φ(.) being an odd monotone nondecreasing function. The resulting bound on is less restrictive than earlier criteria

Hermite polynomials for signal reconstruction from zero-crossings. Part 1:One-dimensional signals

Generalised Hermite polynomials are employed for the reconstruction of an unknown signal from a knowledge of its zero-crossings, under certain conditions on its spatial/spectral width, but dispensing with the assumption of bandlimitedness. A computational implementation of the proposed method is given for one-variable (or one-dimensional) signals, featuring an application of simulated annealing for optimal reconstruction

On the Positivity of Certain Nonlinear Time-Varying Operators

Sufficient conditions are given for the positivity of a composition of two positive operators, one of which is nonlinear and time varying

An exponential stability criterion for certain nonlinear systems

Improved sufficient conditions are derived for the exponential stability of a nonlinear time varying feedback system having a time invariant blockG in the forward path and a nonlinear time varying gain ϕ(.)k(t) in the feedback path. φ(.) being an odd monotone nondecreasing function. The resulting bound on \left( {{{\frac{{dk}}{{dt}}} \mathord{\left/ {\vphantom {{\frac{{dk}}{{dt}}} k}} \right. \kern-\nulldelimiterspace} k}} \right) is less restrictive than earlier criteria

On the stability of a nonlinear system with periodic coefficients

A quasi-geometric stability criterion for feedback systems with a linear time invariant forward block and a periodically time varying nonlinear gain in the feedback loop is developed

On the Stability of a Linear Time-Varying System

A single-loop linear system with a time-invariant stable blockGin the direct path and a time-varying gain in the feedback path is analyzed for asymptotic stability in the Popov framework by way of admitting noncausal "multipliers" in the stability criterion. It is shown that an auto-correlation bound, analogous to O'Shea's cross-correlation bounds [1], results in a constraint on dk/dt more restrictive than that of Gruber and Willems [2]