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The aims of this paper are two-folds. Firstly, we present a model-free algorithm for synthesizing an online controller. Secondly, this algorithm also addresses the issue of switching this controller in closed-loop with a bumpless mechanism. The novelty of this algorithm lies in the fact that we do not use any a priori knowledge of the model of the plant in realtime. We use the mathematical framework...
In this preliminary research we examine the suitability of hierarchical strategies of multi-class support vector machines for classification of induced pluripotent stem cell (iPSC) colony images. The iPSC technology gives incredible possibilities for safe and patient specific drug therapy without any ethical problems. However, growing of iPSCs is a sensitive process and abnormalities may occur during...
Biometric systems accurately recognise/authenticate an individual to access his confidential data/accounts. When multiple traits are fused together at feature/ score/ decision level, it results into highly accurate multimodal systems. This system improvise rate of recognizing an individual. Multiple biometric traits cannot be cloned simultaneously and hence it is highly secured system. The match scores...
The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine...
In this paper, we propose a semiparametric regression model that relates the received signal strength indicators (RSSIs) to the distances separating stationary sensors and moving sensors in a wireless sensor network. This model combines the well-known log-distance theoretical propagation model with a nonlinear fluctuation term, estimated within the framework of kernel-based machines. This leads to...
Recently, the Voice Activity Detection (VAD) algorithms based on machine learning techniques have shown impressive results in the area of speech recognition. In this paper, we present a case study and we discuss the performance of VAD based on Support Vector Machines (SVM) for Distributed Speech Recognition (DSR) system. In this case study, the speech and the non-speech frames are detected from the...
Color image reconstruction provides a measure of the feature representation capability of the moment functions. In this work, we present the quaternion Fourier-Legendre moments in polar pixels, which are computationally faster and have a high-precision compared with other methods. In addition, to improve the performance of the array of polar pixels, we use an inherent property of the Legendre polynomials...
We propose polynomial-time algorithms that sparsify planar and bounded-genus graphs while preserving optimal or near-optimal solutions to Steiner problems. Our main contribution is a polynomial-time algorithm that, given an unweighted graph G embedded on a surface of genus g and a designated face f bounded by a simple cycle of length k, uncovers a set F in E(G) of size polynomial in g and k that contains...
The paper discusses a kernel RX algorithm for hyperspectral target detection. Because it is difficult to estimate the covariance matrix accurately for background areas, directly using the RX Algorithm for hyperspectral target detection is not a good choice in many cases. Therefore, we apply a kernel RX algorithm to our application. The kernel RX algorithm has good nonlinear anomaly detection ability...
Machine Learning methods such as Neural Network (NN) and Support Vector Regression (SVR) have been studied extensively for time series forecasting. Multiple Kernel Learning (MKL) which utilizes SVR as the predictor is yet another recent approaches to choose suitable kernels from a given pool of kernels by means of a linear combination of some base kernels. However, some literatures suggest that this...
A texture descriptor based on a set of indices of degrees of local approximating polynomials is proposed in this paper. An image is split into non-overlapping patches, reshaped into one-dimensional source vectors and convolved with the polynomial approximation kernels of various degrees p. As a result, a set of approximations is obtained. For each element of the source vector, these approximations...
Nonnegative matrix factorization (NMF) is a recent method used to decompose a given data matrix into two nonnegative sparse factors. There are many techniques applied to enhance abilities of NMF, particularly kernel technique which discovering higher-order correlation between data points and obtaining more powerful latent features. This paper presents an overview of kernel methods on NMF along with...
In this paper the alternative method for determination of all possible lower reachability indices has been proposed. Method is based on the extension of parallel digraphs creation algorithm presented previously. As a solution of problem of determination of lower reachability index, method finds all possible finite paths in the digraphs — each of them representing one of the indices. By performing...
Kernel-based methods have been widely used in various machine learning tasks. The performance of these methods strongly relies on the choice of the kernel which represents the similarity between each pair of data points. Therefore, choosing an appropriate kernel function or tuning its parameter(s) is an important issue in the kernel-based methods. Multiple Kernel Learning (MKL) methods have been developed...
In our a previous work we have dealt with the generating function construction for representing the general term of a sequence as a moment like integral where a generating function takes the role of a weight function. We have assumed therein that the each pair of sequence elements satisfy a first order homogeneous linear recursion with variant coefficients. Then we have tried to construct ODE (s)...
We continue the Coxeter spectral study of finite connected loop-free edge-bipartite graphs ?, with m+2 = 3 vertices (a class of signed graphs), started in [SIAM J. Discrete Math., 27 (2013), 827-854] by means of the complex Coxeter spectrum specc ? ? C and presented in our talks given in SYNASC12 and SYNASC13. Here, we study non-negative edge-bipartite graphs of corank two, in the sense that the symmetric...
The research presented focuses on implementation of RF digital predistorters using polynomial optimization techniques. By representing the system with a set of two polynomials, we have been able to apply algebraic techniques resulting in reduction in cost of implementing digital predistorters. To test this approach we have used model of a communication channel using traveling wave tube amplifier and...
Q-Gaussian function has the extensive scope of application compared with Gaussian function. It can become many different radial basis functions when we choice the different parameters. Q-Gaussian is chose as kernel to establish the financial early warning model of listing Corporation in this paper. Through the contrast of the Fisher model based on Gaussian kernel, polynomial kernel and the linear...
Protein-protein interactions (PPIs) are known for its important role in diverse biological processes. One of the crucial issues to understand and classify PPI is to characterize their interfaces in order to discriminate between transient and permanent complexes. The stability of protein-protein interactions depends on the energetic features of interaction surfaces. This work explores the surfaces...
It is commonly known that the success of support vector machines in image classification and annotation it highly dependent on the relevance of the chosen kernels. The latter, defined as symmetric positive semi-definite functions, take high values when images share similar visual content and vice-versa. However, usual kernels relying only on the visual content are not appropriate in order to capture...
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