Search results for "Nonlinear system"

Global linear feedback control for the generalized Lorenz system

2006

Abstract In this paper we show how the chaotic behavior of the Chen system can be controlled via feedback technique. We design both a nonlinear feedback controller and a linear one which globally regulate the closed-loop system states to a given point. We finally show that our approach works also for the whole family of the generalized Lorenz system.

Nonlinear Feedback Control and Stability Analysis of a Proof-of-Work Blockchain

2017

In this paper a novel feedback controller and stability analysis of a blockchain implementation is developed by using a control engineering perspective. The controller output equals the difficulty adjustment in the mining process while the feedback variable is the average block time over a certain time period. The computational power (hash rate) of the miners is considered a disturbance in the model. The developed controller is tested against a simulation model with constant disturbance, step and ramp responses as well as with a high-frequency sinusoidal disturbance. Stability and a fast response is demonstrated in all these cases with a controller which adjusts it's output at every new blo…

Nonlinear radial-harmonic correlation using binary decomposition for scale-invariant pattern recognition

2003

We introduce a new scale-invariant pattern-recognition method that uses nonlinear correlation. We applied several common linear correlations to images decomposed into disjoint binary images, which is very discriminant even when the target is embedded in strong noise. We combine our sliced orthogonal nonlinear generalized correlation method and the radial-harmonic expansion in order to achieve scale-invariant pattern recognition. The information from a radial harmonic for each binary slice of the reference object is combined with binary slices of the target. The method avoids the time-consuming process of finding expansion centers for the radial harmonics. The stability of the correlation pe…

Interlacing multiplexing techniques for optical morphological correlation

2006

We propose a novel approach to implement nonlinear morphological correlation. Previous implementation was based on a time sequential approach that consists on displaying different binary image decomposition in a joint transform correlator adding each joint power spectra sequentially. A second Fourier transformation of the sum of joint power spectra gives the correlation output. In this paper, we propose to interlace the different binary images into one single distribution. Then, we introduce the distribution in a conventional joint transform correlator. The correlation output gives the morphological correlation at a specific location. The advantage is important considering that no sequentia…

Assessment of qualitative judgements for conditional events in expert systems

1991

Comprehensive Strategy for Proton Chemical Shift Prediction: Linear Prediction with Nonlinear Corrections

2014

A fast 3D/4D structure-sensitive procedure was developed and assessed for the chemical shift prediction of protons bonded to sp3carbons, which poses the maybe greatest challenge in the NMR spectral parameter prediction. The LPNC (Linear Prediction with Nonlinear Corrections) approach combines three well-established multivariate methods viz. the principal component regression (PCR), the random forest (RF) algorithm, and the k nearest neighbors (kNN) method. The role of RF is to find nonlinear corrections for the PCR predicted shifts, while kNN is used to take full advantage of similar chemical environments. Two basic molecular models were also compared and discussed: in the MC model the desc…

Weighted nonlinear correlation for controlled discrimination capability

2002

We recently demonstrated the high discrimination capability as well as the high sensitivity to small intensity variations of the sliced orthogonal nonlinear generalized (SONG) correlation. This nonlinear correlation has a correlation matrix representation. Previous papers considered only the principal diagonal elements of the correlation matrix. We propose using the off-diagonal non-zero elements of the SONG correlation matrix in order to achieve variable discrimination performance and controlled detection adapted to the gray-scale variations. Moreover, we introduce negative coefficients in order to improve the discrimination properties of the SONG correlation. To control the degree of reco…

Dynamics of Vertebral Column Observed by Stereovision and Recurrent Neural Network Model

2005

A new non-invasive method for investigation of movement of selected points on the vertebral column is presented. The registration of position of points marked on patient's body is performed by 4 infrared cameras. This experiment enables to reconstruct 3-dimensional trajectories of displacement of marked points. We introduce recurrent neural networks as formal nonlinear dynamical models of each point trajectory. These models are based only on experimental data and are set up of minimal number of parameters. Therefore they are suitable for pattern recognition problems.

Modified LACIF filtering in background disjoint noise

2011

Abstract This work deals with pattern recognition methods based on correlations for images in the presence of noise. We propose a modification of the nonlinear Locally Adaptive Contrast Invariant Filter (LACIF) that yields correlation peaks that are invariant to linear intensity changes of the target but that has some limitations in the presence low variance nonoverlapping background noise. The modification of the filter implies a normalization by a global variance of several distributions. The estimation of the variance distributions is done locally by means of correlations. Experimental results as well as comparisons with the classical matched filter and the common LACIF are given.

Stochastic seismic analysis of offshore towers

1984

After a brief review of the main problems and the most common analysis methods for offshore structures, a method of analysis for offshore towers submerged in water and subjected to strong earthquake motions is proposed. Nonlinear drag effects as well as random non-stationary seismic excitations are considered by means of a linearization technique based on a particular step-by-step procedure. Using a discrete lumped-mass model, the standard deviations of nodal displacements and velocities are evaluated. The probability of not exceeding a defined threshold of nodal displacements is also computed.