An approach based on discrete Karhunen-Loeve transformation of the DS/SS signals is proposed to estimate PN sequence in lower S/N ratio DS/SS signals. Characteristics of self-organization and principle components extr...An approach based on discrete Karhunen-Loeve transformation of the DS/SS signals is proposed to estimate PN sequence in lower S/N ratio DS/SS signals. Characteristics of self-organization and principle components extraction of unsupervised neural networks are exploited adequately. Theoretical analysis and experimental results are provided to show that this approach can work well on the lower S/N ratio input signals.展开更多
Adaptive whitening filters have been proven to be powerful to eliminate narrow band interference in spread spectrum (SS) communication systems. However digital implementation of such kind adaptive filters is difficu...Adaptive whitening filters have been proven to be powerful to eliminate narrow band interference in spread spectrum (SS) communication systems. However digital implementation of such kind adaptive filters is difficult for applications with chip rate as展开更多
In this paper, a new approach is proposed to estimate pseudo noise(PN) sequence in the lower SNR DS/SS signals blindly. This method utilizes the characteristics of self-organization, principal components analysis and ...In this paper, a new approach is proposed to estimate pseudo noise(PN) sequence in the lower SNR DS/SS signals blindly. This method utilizes the characteristics of self-organization, principal components analysis and extraction of unsupervised neural networks adequately, in addition to its higher-speed operation ability, successfully solve the difficult problem about PN sequence blind estimation. The theoretic analysis and experimental results show that this approach can work very well on lower SNR input signals.展开更多
Bacillus subtilis was investigated as production of biosurfactant using a combination based on waste of candy industry and glycerol from biodiesel production process as only substrate. The experimental design chosen f...Bacillus subtilis was investigated as production of biosurfactant using a combination based on waste of candy industry and glycerol from biodiesel production process as only substrate. The experimental design chosen for optimization by response surface methodology was a central composite rotatable design (CCRD) and dry weight (DW) and crude biosurfactant (CB) concentrations were selected as responses in analysis. Two techniques were implemented response surface methodology (RSM) and artificial neural network (ANN). First challenge of study was to assess the effects of the interactions between variables and reach optimum values. With the CCRD results, RSM and ANN models were developed, optimizing the production of biosurfactant. The correlation coefficients (R2) of RSM models explained 88% for DW and 73% for CB of the interactions among substrate concentrations, while ANN models explained 99% for DW and 98% for CB, demonstrating that developed ANN models were more accurate and consistent in predicting optimized conditions than RSM model. The maximum DW and CB produced in the optimum conditions were 25.60 ± 5.0 g/L and 668 ± 40 mg/L, respectively. The crude biosurfactant also showed applications in cases of oil spreading in water due to clear zone produced in Petri dishes assays.展开更多
文摘An approach based on discrete Karhunen-Loeve transformation of the DS/SS signals is proposed to estimate PN sequence in lower S/N ratio DS/SS signals. Characteristics of self-organization and principle components extraction of unsupervised neural networks are exploited adequately. Theoretical analysis and experimental results are provided to show that this approach can work well on the lower S/N ratio input signals.
文摘Adaptive whitening filters have been proven to be powerful to eliminate narrow band interference in spread spectrum (SS) communication systems. However digital implementation of such kind adaptive filters is difficult for applications with chip rate as
文摘In this paper, a new approach is proposed to estimate pseudo noise(PN) sequence in the lower SNR DS/SS signals blindly. This method utilizes the characteristics of self-organization, principal components analysis and extraction of unsupervised neural networks adequately, in addition to its higher-speed operation ability, successfully solve the difficult problem about PN sequence blind estimation. The theoretic analysis and experimental results show that this approach can work very well on lower SNR input signals.
文摘Bacillus subtilis was investigated as production of biosurfactant using a combination based on waste of candy industry and glycerol from biodiesel production process as only substrate. The experimental design chosen for optimization by response surface methodology was a central composite rotatable design (CCRD) and dry weight (DW) and crude biosurfactant (CB) concentrations were selected as responses in analysis. Two techniques were implemented response surface methodology (RSM) and artificial neural network (ANN). First challenge of study was to assess the effects of the interactions between variables and reach optimum values. With the CCRD results, RSM and ANN models were developed, optimizing the production of biosurfactant. The correlation coefficients (R2) of RSM models explained 88% for DW and 73% for CB of the interactions among substrate concentrations, while ANN models explained 99% for DW and 98% for CB, demonstrating that developed ANN models were more accurate and consistent in predicting optimized conditions than RSM model. The maximum DW and CB produced in the optimum conditions were 25.60 ± 5.0 g/L and 668 ± 40 mg/L, respectively. The crude biosurfactant also showed applications in cases of oil spreading in water due to clear zone produced in Petri dishes assays.
