Abstract
In our previous researches, some kinds of neuro-system using multiplayer feedforward network with the sigmoid function were applied to recognize currencies. Although they are effective on known patterns recognition, they suffer from unknown patterns rejection. In this paper, a new activation function is proposed to improve rejection capabilities of the system on the premise of ensuring the effectiveness on known patterns recognition. The simulation shows the effectiveness of this activation function on aspects of rejection for unknown patterns and recognition for known patterns compared with the commonly used sigmoid function.
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Sun, B., Takeda, F. (2004). Proposal of Neural Recognition with Gaussian Function and Discussion for Rejection Capabilities to Unknown Currencies. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30132-5_116
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DOI: https://doi.org/10.1007/978-3-540-30132-5_116
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23318-3
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