Improving performance of neurons by adding colour noise |
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Authors: | Keyvan Aghababaiyan |
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Affiliation: | 1. School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran 14395‐515 Iran |
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Abstract: | Noise is not always an interfering signal which perturbs the system. On the contrary, noise signals can enhance the performance of some non‐linear systems such as stochastic resonance (SR). These systems can detect the weak input signal when it is added to the noise signal. According to this property, SR models play a significant role in the functioning of the brain for detecting weak input signals and synchronisation of neural connections. In this study, the authors model neurons as SR systems where different types of noise, i.e. white noise and pink noise, are employed to amplify the weak nervous signals. They demonstrate colour noise, in particular, pink noise enhances the performance of the SR system to amplify the input signal. Furthermore, pink noise has a wider range of optimum values in comparison to white noise. Therefore, they can conclude that neurons are more sensitive to detect the signals that carry pink noise than signals with white noise or without noise. Hence, the retrieving ability of neurons can be improved by adding pink noise.Inspec keywords: stochastic processes, white noise, neural nets, brain, noise, neurophysiologyOther keywords: interfering signal, particular noise, colour noise, weak nervous signals, pink noise, white noise, SR system, authors model neurons, SR models, noise signal, weak input signal, nonlinear systems |
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