Memristive Chebyshev Neural Network and Its Applications in Function Approximation

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="429402.fig.004a" src="https://static.hindawi.com/articles/mpe/volume-2013/429402/figures/429402.fig.004a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>  Relationship between training error and the number of learning</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="429402.fig.004b" src="https://static.hindawi.com/articles/mpe/volume-2013/429402/figures/429402.fig.004b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b> Relationship between memristive weights and the number of learning</td></tr></table></td></tr><tr class="fig-image" id="c"><td><img alt="429402.fig.004c" src="https://static.hindawi.com/articles/mpe/volume-2013/429402/figures/429402.fig.004c.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(c) </b> The final memristive weights in the hidden layer</td></tr></table></td></tr><tr class="fig-image" id="d"><td><img alt="429402.fig.004d" src="https://static.hindawi.com/articles/mpe/volume-2013/429402/figures/429402.fig.004d.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(d) </b> The approximation curve</td></tr></table></td></tr></table>

<table>Simulation results for memristive BP algorithm. </table>

Mathematical Problems in Engineering

fig4

Figure 4

Figure 4: Memristive Chebyshev Neural Network and Its Applications in Function Approximation 