Search results for "time delay"
showing 10 items of 72 documents
A NEURAL NETWORK PRIMER
1994
Neural networks are composed of basic units somewhat analogous to neurons. These units are linked to each other by connections whose strength is modifiable as a result of a learning process or algorithm. Each of these units integrates independently (in paral lel) the information provided by its synapses in order to evaluate its state of activation. The unit response is then a linear or nonlinear function of its activation. Linear algebra concepts are used, in general, to analyze linear units, with eigenvectors and eigenvalues being the core concepts involved. This analysis makes clear the strong similarity between linear neural networks and the general linear model developed by statisticia…
H<inf>&#x221E;</inf> control for stochastic switched delay systems with missing measurements: An average dwell time approach
2012
In this paper, the problem of non-fragile observer-based H ∞ control for discrete-time switched delay systems is investigated. Both data missing and time delays are taken into account in the links from sensors to observers and from controllers to actuators. Such problem is transformed into an H ∞ control problem for stochastic switched delay systems. Average dwell time (ADT) approach is used to obtain sufficient conditions on the solvability of such problems. An example is provided to show the effectiveness of the proposed method.
REM near-IR and optical multiband observations of PKS 2155-304 in 2005
2007
Spectral variability is the main tool for constraining emission models of BL Lac objects. By means of systematic observations of the BL Lac prototype PKS 2155-304 in the infrared-optical band, we explore variability on the scales of months, days and hours. We made our observations with the robotic 60 cm telescope REM located at La Silla, Chile. VRIJHK filters were used. PKS 2155-304 was observed from May to December 2005. The wavelength interval explored, the total number of photometric points and the short integration time render our photometry substantially superior to previous ones for this source. On the basis of the intensity and colour we distinguish three different states of the sour…
Asynchronously switched control of discrete impulsive switched systems with time delays
2013
This paper is concerned with the stabilization problem for a class of uncertain discrete impulsive switched delay systems under asynchronous switching. The so-called asynchronous switching means that the switches between the candidate controllers and system modes are asynchronous. By using the average dwell time (ADT) approach, sufficient conditions for the existence of an asynchronously switched controller is derived such that the resulting closed-loop system is exponentially stable. The desired controller gains and the admissible switching signals are obtained in terms of a set of matrix inequalities. A numerical example is given to illustrate the effectiveness of the proposed method.
Synchronization of Uncertain Neural Networks with H8 Performance and Mixed Time-Delays
2011
An exponential H8 synchronization method is addressed for a class of uncertain master and slave neural networks with mixed time-delays, where the mixed delays comprise different neutral, discrete and distributed time-delays. An appropriate discretized Lyapunov-Krasovskii functional and some free weighting matrices are utilized to establish some delay-dependent sufficient conditions for designing a delayed state-feedback control as a synchronization law in terms of linear matrix inequalities under less restrictive conditions. The controller guarantees the exponential H8 synchronization of the two coupled master and slave neural networks regardless of their initial states. Numerical simulatio…
A system based on neural architectures for the reconstruction of 3-D shapes from images
1991
The connectionist approach to the recovery of 3-D shape information from 2-D images developed by the authors, is based on a system made up by two cascaded neural networks. The first network is an implementation of the BCS, an architecture which derives from a biological model of the low level visual processes developed by Grossberg and Mingolla: this architecture extracts a sort of brightness gradient map from the image. The second network is a backpropagation architecture that supplies an estimate of the geometric parameters of the objects in the scene under consideration, starting from the outputs of the BCS. A detailed description of the system and the experimental results obtained by si…
Compensated transfer entropy as a tool for reliably estimating information transfer in physiological time series
2013
We present a framework for the estimation of transfer entropy (TE) under the conditions typical of physiological system analysis, featuring short multivariate time series and the presence of instantaneous causality (IC). The framework is based on recognizing that TE can be interpreted as the difference between two conditional entropy (CE) terms, and builds on an efficient CE estimator that compensates for the bias occurring for high dimensional conditioning vectors and follows a sequential embedding procedure whereby the conditioning vectors are formed progressively according to a criterion for CE minimization. The issue of IC is faced accounting for zero-lag interactions according to two a…
Dynamic Pattern Recognition in Sport by Means of Artificial Neural Networks
2008
Behavioural processes like those in sports, motor activities or rehabilitation are often the object of optimization methods. Such processes are often characterized by a complex structure. Measurements considering them may produce a huge amount of data. It is an interesting challenge not only to store these data, but also to transform them into useful information. Artificial Neural Networks turn out to be an appropriate tool to transform abstract numbers into informative patterns that help to understand complex behavioural phenomena. The contribution presents some basic ideas of neural network approaches and several examples of application. The aim is to give an impression of how neural meth…
Non-fragile H ∞ control for switched stochastic delay systems with application to water quality process
2013
SUMMARY In this paper, the problem of non-fragile observer-based H ∞ control for discrete-time switched delay systems is investigated. Both data missing and time delays are taken into account in the links from sensors to observers and from controllers to actuators. Because data missing satisfies the Bernoulli distribution, such problem is transformed into an H ∞ control problem for stochastic switched delay systems. Average dwell time approach is used to obtain sufficient conditions on the solvability of such problems. A numerical example and a real example for water quality control are provided to illustrate the effectiveness and potential applications of the proposed techniques. Copyrig…
Prefiltering for pattern recognition using wavelet transform and neural networks
2003
Publisher Summary Neural networks are built from simple units interlinked by a set of weighted connections. Generally, these units are organized in layers. Each unit of the first layer (input layer) corresponds to a feature of a pattern that is to be analyzed. The units of the last layer (output layer) produce a decision after the propagation of information. Before feeding the computational data to neural networks, the signal must undergo a preprocessing in order to (1) define the initial transformation to represent the measured signal, (2) retain important features for class discrimination and discard that is irrelevant, and (3) reduce the volume of data to be processed, for example, data …