We propose a new algorithm for the non-negative ICA problem, based on the rotational nature of optimization over a set of square orthogonal (orthonormal) matrices W, i.e. where W W = WW = In. Using a truncated Fourier expansion of J(t), we obtain a Newton-like update step along the steepest-descent geodesic, which automatically approximates to a usual (Taylor expansion) Newton update step near ...

In this paper we propose a new algorithm for the clustering of signals using incomplete independent component analysis (ICA). In the first step we apply the ICA to the dataset without dimension reduction, in the second step we reduce the dimension of the data to find clusters of independent components that are similar in their entries in the mixture matrix found by the ICA. We demonstrate that ...

The Vehicle Routing Problem (VRP), a famous problem of operation research, holds a central place in combinatorial optimization problems. In this problem, a fleet vehicles with Q capacity start to move from depot and return after servicing to customers in which visit only ones each customer and load more than its capacity not at all. The objective is to minimize the number of used vehicles and t...

Minimization of arrival time at scenes plays an essential role to help injured people in emergency events. This can be undertaken through mathematical programming models, called emergency medical services location problem, and solved by conventional exact algorithms or by recent meta-heuristic methods as well. Meta-heuristic algorithms have recently been realized to be more efficient in the sen...

In this paper, a novel algorithm for the load flow analysis problem in an islanded microgrid is proposed. The problem is modeled without any slack bus by considering the steady state frequency as one of the load flow variables. To model different control modes of DGs, such as droop, PV and PQ, in an islanded microgrid, a new formula for load flow equations is proposed. A hybrid optimization alg...

Geometric independent component analysis (ICA) uses a weight update rule that is very similar to the self-organizing map (SOM) learning rule in the case of a trivial neighborhood function. In this paper we use this fact and present a new geometric ICA algorithm that uses a SOM for learning. The separation qualiry is better in comparison to other geometric algorithms, but the computational cost ...

We investigate automatic classification of posts to Internet forums. We use collective classification methods, which simultaneously classify related objects — in our case, the posts in a thread. Specifically, we compare the Iterative Classification Algorithm (ICA) with Conditional Random Fields and with conventional classifiers (k-Nearest Neighbours and Support Vector Machines). The ICA algorit...

Mutual information (MI) is a common criterion in independent component analysis (ICA) optimization. MI is derived from probability density functions (PDF). There are scenarios in which assuming a parametric form for the PDF leads to poor performance. Therefore, the need arises for non-parametric PDF and MI estimation. Existing nonparametric algorithms suffer from high complexity, particularly i...

In this paper we consider the blind source separation (BSS) of complex sinusoidal signals with different frequencies. We introduce a novel ICA (Independent Component Analysis) algorithm for the BSS. ICA requires no prior information of the source signals because it employs only the statistical independence of them. We have already confirmed that ICA was successfully applied to a deterministic s...

The conventional detection process of direct sequence code division multiple access (DS-CDMA) is limited by multiple access interference (MAI) due to loss of orthogonality between spreading waveforms in multipath propagation channel environment.. In this paper RADICAL Independent Component Analysis (ICA) algorithm is proposed for detection of DS-CDMA signals and compared with FastICA, JADE ICA ...