In this paper, a new feature extraction algorithm considering both two-directional two-dimensional principal component analysis ((2D)2PCA) and independent component analysis(ICA), called (2D)2PCA-ICA, is proposed for face representation. This algorithm analyzes the principal components of image vectors on 2D matrices by simultaneously considering the row and column directions as opposed to the ...

Traditional independent component analysis may produce different results in the repeated calculations for their statistical characteristics, and thus they are unreliable and unstable. This paper introduces a novel ICA algorithm which enhances the separation performance and stability by clustering evaluation. Firstly, the improved ICA algorithm runs a single ICA algorithm for several times with ...

Independent component analysis (ICA) has many practical applications in the fields of signal and image processing and several ICA learning algorithms have been constructed via the selection of model probability density functions. However, there is still a lack of deep mathematical theory to validate these ICA algorithms, especially for the general case that superand sub-Gaussian sources coexist...

This paper presents a new algorithm for the independent components analysis (ICA) problem based on efficient spacings estimates of entropy. Like many previous methods, we minimize a standard measure of the departure from independence, the estimated Kullback-Leibler divergence between a joint distribution and the product of its marginals. To do this, we use a consistent and rapidly converging en...

The fast fixed-point independent component analysis (ICA) algorithm has been widely used in various applications because of its fast convergence and superior performance. However, in a highly dynamic environment, real-time adaptation is necessary to track the variations of the mixing matrix. In this scenario, the gradient-based online learning algorithm performs better, but its convergence is s...

This paper presents a new mathematical model for a hybrid flow shop scheduling problem with multiprocessor tasks in which sequence dependent set up times and preemption are considered. The objective is to minimize the weighted sum of makespan and maximum tardiness. Three meta-heuristic methods based on genetic algorithm (GA), imperialist competitive algorithm (ICA) and a hybrid approach of GA a...

contamination of water by heavy metals is a global problem. nowadays everybody knows that heavy metal ions consist of iron, lead, manganese, zinc, copper, cadmium, and nickel and so on they are common contaminants in wastewater and known to be toxic and carcinogenic that lead to many problems for human and water environment. in this research, experiments have been performed in the batch system ...

Among all wavelet transform and zero-tree quantization based image coding algorithms, set partitioning in hierarchical trees (SPIHT) is well known for its simplicity and efficiency. But theoretical analysis and experimental results have shown there are still some key points need to be further improved. This paper proposes a coefficient Statistic based Modified SPIHT Lossless Image Compression A...

This paper derives a new algorithm that performs independent component analysis (ICA) by optimizing the contrast function of the RADICAL algorithm. The core idea of the proposed optimization method is to combine the global search of a good initial condition with a gradient-descent algorithm. This new ICA algorithm performs faster than the RADICAL algorithm (based on Jacobi rotations) while stil...

In this paper, it is shown that independent component analysis (ICA) of sparse signals (sparse ICA) can be seen as a cluster-wise principal component analysis (PCA). Consequently, Sparse ICA may be done by a combination of a clustering algorithm and PCA. For the clustering part, we use, in this paper, an algorithm inspired from K-means. The final algorithm is easy to implement for any number of...