Based on potted plant experiment, BP-artifieial neural network was used to simulate crop evapotranspiration and 3 kinds of artificial neural network models were constructed as ET1 （meteorological factors）, ET2（ met...Based on potted plant experiment, BP-artifieial neural network was used to simulate crop evapotranspiration and 3 kinds of artificial neural network models were constructed as ET1 （meteorological factors）, ET2（ meteorological factors and sowing days） and ET3 （meteorological factors, sowing days and water content）. And the predicted result was compared with actual value ET that was obtained by weighing method. The results showed that the ET3 model had higher calculation precision and an optimum BP-artificial neural network model for calculating crop evapotranspiration.展开更多
We find that the fractional-order Hindmarsh-Rose model neuron demonstrates various types of firing behavior as a function of the fractional order in this study.There exists a clear difference in the bifurcation diagra...We find that the fractional-order Hindmarsh-Rose model neuron demonstrates various types of firing behavior as a function of the fractional order in this study.There exists a clear difference in the bifurcation diagram between the fractional-order Hindmarsh-Rose model and the corresponding integer-order model even though the neuron undergoes a Hopf bifurcation to oscillation and then starts a period-doubling cascade to chaos with the decrease of the externally applied current.Interestingly,the discharge frequency of the fractional-order Hindmarsh-Rose model neuron is greater than that of the integer-order counterpart irrespective of whether the neuron exhibits periodic or chaotic firing.Then we demonstrate that the firing behavior of the fractional-order Hindmarsh-Rose model neuron has a higher complexity than that of the integer-order counterpart.Also,the synchronization phenomenon is investigated in the network of two electrically coupled fractional-order model neurons.We show that the synchronization rate increases as the fractional order decreases.展开更多
In this paper, we address the characteristic model-based discrete-time consensus problem of networked robotic manipulators with dynamic uncertainties. The research objective is to achieve joint-position consensus of m...In this paper, we address the characteristic model-based discrete-time consensus problem of networked robotic manipulators with dynamic uncertainties. The research objective is to achieve joint-position consensus of multiple robotic agents interconnected on directed graphs containing a spanning tree. A novel characteristic model-based distributed adaptive control scenario is proposed with a state-relied projection estimation law and a characteristic model-based distributed controller. The performance analysis is also unfolded where the uniform ultimate boundedness(UUB) of consensus errors is derived by resorting to the discrete-time-domain stability analysis tool and the graph theory. Finally, numerical simulations illustrate the effectiveness of the proposed theoretical strategy.展开更多
基金Supported by the National Natural Science Foundation of China(50609022)~~
文摘Based on potted plant experiment, BP-artifieial neural network was used to simulate crop evapotranspiration and 3 kinds of artificial neural network models were constructed as ET1 （meteorological factors）, ET2（ meteorological factors and sowing days） and ET3 （meteorological factors, sowing days and water content）. And the predicted result was compared with actual value ET that was obtained by weighing method. The results showed that the ET3 model had higher calculation precision and an optimum BP-artificial neural network model for calculating crop evapotranspiration.
基金supported by the National Natural Science Foundation of China(Grant Nos.11272241and 10972170)
文摘We find that the fractional-order Hindmarsh-Rose model neuron demonstrates various types of firing behavior as a function of the fractional order in this study.There exists a clear difference in the bifurcation diagram between the fractional-order Hindmarsh-Rose model and the corresponding integer-order model even though the neuron undergoes a Hopf bifurcation to oscillation and then starts a period-doubling cascade to chaos with the decrease of the externally applied current.Interestingly,the discharge frequency of the fractional-order Hindmarsh-Rose model neuron is greater than that of the integer-order counterpart irrespective of whether the neuron exhibits periodic or chaotic firing.Then we demonstrate that the firing behavior of the fractional-order Hindmarsh-Rose model neuron has a higher complexity than that of the integer-order counterpart.Also,the synchronization phenomenon is investigated in the network of two electrically coupled fractional-order model neurons.We show that the synchronization rate increases as the fractional order decreases.
基金supported by the National Natural Science Foundation of China(Grant Nos.6133300861273153&61304027)
文摘In this paper, we address the characteristic model-based discrete-time consensus problem of networked robotic manipulators with dynamic uncertainties. The research objective is to achieve joint-position consensus of multiple robotic agents interconnected on directed graphs containing a spanning tree. A novel characteristic model-based distributed adaptive control scenario is proposed with a state-relied projection estimation law and a characteristic model-based distributed controller. The performance analysis is also unfolded where the uniform ultimate boundedness(UUB) of consensus errors is derived by resorting to the discrete-time-domain stability analysis tool and the graph theory. Finally, numerical simulations illustrate the effectiveness of the proposed theoretical strategy.
