In the osmotic dehydration process of food,on-line estimation of concentrations of two components in ternary solution with NaCl and sucrose was performed based on multi-functional sensing technique.Moving Least Square...In the osmotic dehydration process of food,on-line estimation of concentrations of two components in ternary solution with NaCl and sucrose was performed based on multi-functional sensing technique.Moving Least Squares were adopted in approximation procedure to estimate the viscosity of such interested ternary solution with the given data set.As a result,in one mode of using total experimental data as calibration data and validation data,the relative deviations of estimated viscosities are less than ±1.24%.In the other mode,by taking total experimental data except the ones for estimation as calibration data,the relative deviations are less than ±3.47%.In the same way,the density of ternary solution can be also estimated with deviations less than ± 0.11% and ± 0.30% respectively in these two models.The satisfactory and accurate results show the extraordinary efficiency of Moving Least Squares behaved in signal approximation for multi-functional sensors.展开更多
The local well-posedness of the Cauchy problem for the Hirota equation is established for low regularity data in Sobolev spaces Hs(s ≥ -1-4). Moreover, the global well-posedness for L2 data follows from the local wel...The local well-posedness of the Cauchy problem for the Hirota equation is established for low regularity data in Sobolev spaces Hs(s ≥ -1-4). Moreover, the global well-posedness for L2 data follows from the local well-posedness and the conserved quantity. For data in Hs(s ＞ 0), the global well-posedness is also proved. The main idea is to use the generalized trilinear estimates, associated with the Fourier restriction norm method.展开更多
This paper addresses the problem of joint angle and delay estimation(JADE) in a multipath communication scenario. A low-complexity multi-way compressive sensing(MCS) estimation algorithm is proposed. The received data...This paper addresses the problem of joint angle and delay estimation(JADE) in a multipath communication scenario. A low-complexity multi-way compressive sensing(MCS) estimation algorithm is proposed. The received data are firstly stacked up to a trilinear tensor model. To reduce the computational complexity,three random compression matrices are individually used to reduce each tensor to a much smaller one. JADE then is linked to a low-dimensional trilinear model. Our algorithm has an estimation performance very close to that of the parallel factor analysis(PARAFAC) algorithm and automatic pairing of the two parameter sets. Compared with other methods, such as multiple signal classification(MUSIC), the estimation of signal parameters via rotational invariance techniques(ESPRIT), the MCS algorithm requires neither eigenvalue decomposition of the received signal covariance matrix nor spectral peak searching. It also does not require the channel fading information, which means the proposed algorithm is blind and robust, therefore it has a higher working efficiency.Simulation results indicate the proposed algorithm have a bright future in wireless communications.展开更多
基金Sponsored by the National Natural Science Foundation of China(Grant No.60672008)the Space Technology Innovation Foundation of China
文摘In the osmotic dehydration process of food,on-line estimation of concentrations of two components in ternary solution with NaCl and sucrose was performed based on multi-functional sensing technique.Moving Least Squares were adopted in approximation procedure to estimate the viscosity of such interested ternary solution with the given data set.As a result,in one mode of using total experimental data as calibration data and validation data,the relative deviations of estimated viscosities are less than ±1.24%.In the other mode,by taking total experimental data except the ones for estimation as calibration data,the relative deviations are less than ±3.47%.In the same way,the density of ternary solution can be also estimated with deviations less than ± 0.11% and ± 0.30% respectively in these two models.The satisfactory and accurate results show the extraordinary efficiency of Moving Least Squares behaved in signal approximation for multi-functional sensors.
文摘The local well-posedness of the Cauchy problem for the Hirota equation is established for low regularity data in Sobolev spaces Hs(s ≥ -1-4). Moreover, the global well-posedness for L2 data follows from the local well-posedness and the conserved quantity. For data in Hs(s ＞ 0), the global well-posedness is also proved. The main idea is to use the generalized trilinear estimates, associated with the Fourier restriction norm method.
基金supported by the National Natural Science Foundation of China(6107116361271327+4 种基金61471191)the Fundamental Research Funds for the Central Universities(NP2015504)the Jiangsu Innovation Program for Graduate Education(KYLX 0277)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PADA)the Funding for Outstanding Doctoral Dissertation in NUAA(BCXJ14-08)
文摘This paper addresses the problem of joint angle and delay estimation(JADE) in a multipath communication scenario. A low-complexity multi-way compressive sensing(MCS) estimation algorithm is proposed. The received data are firstly stacked up to a trilinear tensor model. To reduce the computational complexity,three random compression matrices are individually used to reduce each tensor to a much smaller one. JADE then is linked to a low-dimensional trilinear model. Our algorithm has an estimation performance very close to that of the parallel factor analysis(PARAFAC) algorithm and automatic pairing of the two parameter sets. Compared with other methods, such as multiple signal classification(MUSIC), the estimation of signal parameters via rotational invariance techniques(ESPRIT), the MCS algorithm requires neither eigenvalue decomposition of the received signal covariance matrix nor spectral peak searching. It also does not require the channel fading information, which means the proposed algorithm is blind and robust, therefore it has a higher working efficiency.Simulation results indicate the proposed algorithm have a bright future in wireless communications.
