Fetal electrocardiograms (FECG) contain important indications about the health and condition of the fetus. In this respect, it is crucial to apply a robust algorithm to ECG data for extraction of the FECG signal. Most of the independent component analysis (ICA) algorithms used for this purpose rely on simple statistical models. Such algorithms can fail to separate desired signals when the assum...

Optimization of the exploitation operation is one of the most important issues facing the mining engineers. Since several technical and economic parameters depend on the cut-off grade, optimization of this parameter is of particular importance. The aim of this optimization is to maximize the net present value (NPV). Since the objective function of this problem is non-linear, three methods can b...

In textile industry, marker planning is one of the main operations in the cutting fabric stage. Marker packing is usually used to maximize cloth exploitation and minimize its waste. In this research, a method is used based on new found meta-heuristic imperialist competitive algorithm (ICA) and Bottom-Left-Fill Algorithm (BLF) to achieve optimal marker packing. Function of the proposed method wa...

Commercial cellular networks, like the systems based on DS-CDMA, face many types of interferences such as multi-user interference inside each sector in a cell to interoperate interference. Independent Component Analysis (ICA) has been used as an advanced preprocessing tool for blind suppression of interfering signals in DS-CDMA communication systems. The role of ICA is to provide an interferenc...

the traveling salesman problem (tsp) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. the tsp is probably the most famous and extensively studied problem in the field of combinatorial optimization. because this problem is an np-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...

Independent component analysis (ICA) is vital for unsupervised learning and blind source separation (BSS). The ICA unsupervised learning procedure attempts to demix the observation vectors and identify the salient features or mixture sources. This work presents a novel contrast function for evaluating the dependence among sources. A convex divergence measure is developed by applying the convex ...

Synthetic aperture radar (SAR) imaging has the characteristics of acquiring remote sensing data under all weather and all time. So SAR image change detection techniques have large advantage in abruptly natural and man-made disaster. Inherent speckle noise of SAR image badly obstructs the applications for SAR image change detection. SAR image belongs to non-Gaussian distribution in general, whic...

Algebraic Independent Component Analysis (AICA) is a new ICA algorithm that exploits algebraic operations and vectordistance measures to estimate the unknown mixing matrix in a scaled algebraic domain. AICA possesses stability and convergence properties similar to earlier proposed geometic ICA (geo-ICA) algorithms, however, the choice of the proposed algebraic measures in AICA has several advan...