For the nearly exponential type of feedforward neural networks （neFNNs）, it is revealed the essential order of their approximation. It is proven that for any continuous function defined on a compact set of Rd, there...For the nearly exponential type of feedforward neural networks （neFNNs）, it is revealed the essential order of their approximation. It is proven that for any continuous function defined on a compact set of Rd, there exists a three-layer neFNNs with fixed number of hidden neurons that attain the essential order. When the function to be approximated belongs to the α-Lipschitz family （0 〈α≤ 2）, the essential order of approxi- mation is shown to be O（n^-α） where n is any integer not less than the reciprocal of the predetermined approximation error. The upper bound and lower bound estimations on approximation precision of the neFNNs are provided. The obtained results not only characterize the intrinsic property of approximation of the neFNNs, but also uncover the implicit relationship between the precision （speed） and the number of hidden neurons of the neFNNs.展开更多
The equilibrium and kinetic characteristics of the adsorption of erythromycin to Sepabeads SP825 were determined.The equilibrium data in a batch system was well described by a Langmuir isotherm.The separation performa...The equilibrium and kinetic characteristics of the adsorption of erythromycin to Sepabeads SP825 were determined.The equilibrium data in a batch system was well described by a Langmuir isotherm.The separation performance was investigated in a fixed-bed system with respect to the adsorption superficial velocity,ionic strength and pH.A mathematical model was used to simulate the mass transfer mechanism,taking film mass transfer,pore diffusion and axial dispersion into account.The model predictions were consistent with the experi-mental data and were consequently used to determine the mass transfer coefficients.展开更多
基金the National Natural Science Foundation of China （Grant Nos. 10371097 , 70531030）.
文摘For the nearly exponential type of feedforward neural networks （neFNNs）, it is revealed the essential order of their approximation. It is proven that for any continuous function defined on a compact set of Rd, there exists a three-layer neFNNs with fixed number of hidden neurons that attain the essential order. When the function to be approximated belongs to the α-Lipschitz family （0 〈α≤ 2）, the essential order of approxi- mation is shown to be O（n^-α） where n is any integer not less than the reciprocal of the predetermined approximation error. The upper bound and lower bound estimations on approximation precision of the neFNNs are provided. The obtained results not only characterize the intrinsic property of approximation of the neFNNs, but also uncover the implicit relationship between the precision （speed） and the number of hidden neurons of the neFNNs.
文摘The equilibrium and kinetic characteristics of the adsorption of erythromycin to Sepabeads SP825 were determined.The equilibrium data in a batch system was well described by a Langmuir isotherm.The separation performance was investigated in a fixed-bed system with respect to the adsorption superficial velocity,ionic strength and pH.A mathematical model was used to simulate the mass transfer mechanism,taking film mass transfer,pore diffusion and axial dispersion into account.The model predictions were consistent with the experi-mental data and were consequently used to determine the mass transfer coefficients.
