An Improved ICA Algorithm Based on the Negative Entropy and Simulated Annealing Algorithm

2013 ◽  
Vol 411-414 ◽  
pp. 1125-1128 ◽  
Author(s):  
Hong Yi Li ◽  
Meng Ye ◽  
Di Zhao

The Independent Component Analysis (ICA) is a classical algorithm for exploring statistically independent non-Gaussian signals from multi-dimensional data, which has a wide range of applications in engineering, for instance, the blind source separation. The classical ICA measures the Gaussian characteristic by kurtosis, which has the following two disadvantages. Firstly, the kurtosis relies on the value of samples, and is not robust to outliers. Secondly, the algorithm often falls into local optima. To address these drawbacks, we replace the kurtosis by negative entropy, utilize the simulated annealing algorithm for optimization, and finally propose an improved ICA algorithm. Experimental results demonstrate that the proposed algorithm outperforms the classical ICA in its robustness to outliers and convergent rate.

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xianzhe Meng

This paper introduces the basic principle and application process of simulated annealing algorithm and improves the simulated annealing algorithm so that it can converge faster to get the new parameters of cultural and creative product design and make it more in line with the reality of engineering optimization. In the cultural creative industry, it is necessary to use the creatorʼs creativity and technology to derive and develop the original cultural resources with the help of various materialization means, to refine the abstract and profound contents of cultural resources to make them more visualized, and to produce products with both spiritual and economic values through the multiple development and utilization of their intellectual property contents. By studying the feasibility analysis of the cultural and creative design, the design positioning of the cultural and creative products is determined. In this article, we use the simulated annealing method to simulate and analyse the condition values in the design process of cultural creative products. As the Internet era progresses, people have more diversified requirements for cultural and creative products, and they need to have innovative ideas to follow the trend, so the design of cultural and creative products can spread culture through different design expressions and media. As one of the important pillar industries for future development, cultural and creative products are characterized by a wide range of styles and practicality, which meet the aesthetic needs and fashion trends of modern people.


Author(s):  
Safiye Turgay

Facility layout design problem considers the departments’ physcial layout design with area requirements in some restrictions such as material handling costs, remoteness and distance requests. Briefly, facility layout problem related to optimization of the layout costs and working conditions. This paper proposes a new multi objective simulated annealing algorithm for solving of the unequal area in layout design. Using of the different objective weights are generated with entropy approach and used in the alternative layout design. Multi objective function takes into the objective function and constraints. The suggested heuristic algorithm used the multi-objective parameters for initialization. Then prefered the entropy approach determines the weight of the objective functions. After the suggested improved simulated annealing approach applied to whole developed model. A multi-objective simulated annealing algorithm is implemented to increase the diversity and reduce the chance of getting layout conditions in local optima.


2013 ◽  
Vol 4 (2) ◽  
pp. 20-28
Author(s):  
Farhad Soleimanian Gharehchopogh ◽  
Hadi Najafi ◽  
Kourosh Farahkhah

The present paper is an attempt to get total minimum of trigonometric Functions by Simulated Annealing. To do so the researchers ran Simulated Annealing. Sample trigonometric functions and showed the results through Matlab software. According the Simulated Annealing Solves the problem of getting stuck in a local Maxterm and one can always get the best result through the Algorithm.


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