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Break detection for WDM-PON needed to solve the multi-branch; node density problem for the realization of high-precision positioning of each branch proposed a breakpoint detection method based broadband chaotic light lasers. On the basis of analyzing the characteristics of broadband chaotic sources on a preliminary simulation results show that this method can be highly accurate positioning WDM-PON...
A new olfactory receptor model based on chaos is proposed in this paper. Simulating real olfactory receptor, the new olfactory receptor model is in a chaotic state as the basic state when there is no stimulus. It can be in active state when there is stimulus. Compared with K0 model, Gaussian noise is no need to the new model, which simplifies the olfactory nervous system model. Experimental results...
This paper discusses a method for chaotic time series prediction based on radial basis function (RBF) neural network. The number of input nodes for RBF is determined by embedding dimension based on chaotic phase-space reconstruction. Both Grassberger--Procaccia algorithm and Takens' method are employed to calculate minimal embedding dimension of chaotic time series. Finally, the prediction accuracy...
Based on studies of the biological olfactory system, a chaotic neural network model called a K-set has been constructed. This nonlinear neural network is trained to sustain a landscape of chaotic attractors for use in signal processing. Based on the idea of image partition and the discrete wavelet transform (DWT), this paper applies the chaotic neural network to face recognition. Experimental results...
Based on the study of biological olfactory system, a chaotic neural network model called K set model has been setup. This chaotic neural network has potential on pattern recognition while presenting novel chaotic concept for signal processing. This paper studies the characteristics of the K set models and applies it to face recognition. Experimental results show that the chaotic model based on biological...
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