A proposed model of human consciousness system with applications in pattern recognition

K. Le
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Abstract

Human recognition is a complex, efficient process which, for thousands of years, people have tried to analyse but have not yet fully understood. Recently, with advances in psychology, medicine and computer engineering in some research fields such as neural networks, fuzzy set theory, genetic algorithms, etc., people have tried to simulate the human brain and received significant results in the pattern recognition field. This paper proposes a model of a human consciousness system with applications in pattern recognition. The model explains how our brain saves, extracts and retrieves data. The model can recognise patterns with noise. Furthermore, when part of the model is damaged, the model can be required and re-used. An implementation of the model and some experimental results are also presented.
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一种人类意识系统模型及其在模式识别中的应用
人类的识别是一个复杂而高效的过程,几千年来,人们一直试图对其进行分析,但尚未完全理解。近年来,随着心理学、医学和计算机工程在神经网络、模糊集理论、遗传算法等一些研究领域的进展,人们尝试模拟人脑,并在模式识别领域取得了显著成果。提出了一种在模式识别中应用的人类意识系统模型。该模型解释了我们的大脑如何保存、提取和检索数据。该模型可以识别有噪声的模式。此外,当模型的一部分损坏时,可以重新使用模型。最后给出了模型的实现和一些实验结果。
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