Search results for "Linea"

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

Feature extraction from remote sensing data using Kernel Orthonormalized PLS

2007

This paper presents the study of a sparse kernel-based method for non-linear feature extraction in the context of remote sensing classification and regression problems. The so-called kernel orthonormalized PLS algorithm with reduced complexity (rKOPLS) has two core parts: (i) a kernel version of OPLS (called KOPLS), and (ii) a sparse (reduced) approximation for large scale data sets, which ultimately leads to rKOPLS. The method demonstrates good capabilities in terms of expressive power of the extracted features and scalability.

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…

Further Results on Modeling, Analysis, and Control Synthesis for Offshore Wind Turbine Systems

2014

Renewable energy is a hot topic all over the world. Nowadays, there are several sustainable renewable power solutions out there; hydro, wind, solar, wave, and biomass to name a few. Most countries have a tendency to want to become greener. In the past, all new wind parks were installed onshore. During the last decade, more and more wind parks were installed offshore, in shallow water. This chapter investigates a comparative study on the modeling, analysis, and control synthesis for the offshore wind turbine systems. More specifically, an \( {\mathcal{H}}_{\infty } \) static output-feedback control design with constrained information is designed. Constrained information indicates that a rema…

Flexible design of multifocal metalenses based on autofocused Airy beams

2018

Extreme miniaturization of on-demand optical devices such as ultrathin lenses is currently leading to significant advancements in manufacturing novel materials and nanotechnologies. Flexibility and tunability of engineered layouts enable efficient integration of complex photonic modules. In this regard, here we propose an autofocused Airy (AFA)-based metalens that operates, depending on the molded phase profile, as a multifocal focusing lens, which to the best of our knowledge has not been reported before. To do this, we call attention to the fact that the two conjugate focal points of an AFA beam can be brought into real space by applying a proper convex lens phase profile. Considering ful…

Evaluating Classifiers for Mobile-Masquerader Detection

2006

As a result of the impersonation of a user of a mobile terminal, sensitive information kept locally or accessible over the network can be abused. The means of masquerader detection are therefore needed to detect the cases of impersonation. In this paper, the problem of mobile-masquerader detection is considered as a problem of classifying the user behaviour as originating from the legitimate user or someone else. Different behavioural characteristics are analysed by designated one-class classifiers whose classifications are combined. The paper focuses on selecting the classifiers for mobile-masquerader detection. The selection process is conducted in two phases. First, the classification ac…

On the Benefits of Random Linear Coding for Unicast Applications in Disruption Tolerant Networks

2006

In this paper, we investigate the benefits of using a form of network coding known as Random Linear Coding (RLC) for unicast communications in a mobile Disruption Tolerant Network (DTN) under epidemic routing. Under RLC, DTN nodes store and then forward random linear combinations of packets as they encounter other DTN nodes. We first consider the case where there is a single block of packets propagating in the network and then consider the case where blocks of K packets arrive according to a Poisson arrival process. Our performance metric of interest is the delay until the last packet in a block is delivered. We show that for the single block case, when bandwidth is constrained, applying RL…

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.