Although fuzzy set concepts have evolved,neutrosophic sets are attractingmore attention due to the greater power of the structure of neutrosophic sets.The ability to account for components that are true,false or neith...Although fuzzy set concepts have evolved,neutrosophic sets are attractingmore attention due to the greater power of the structure of neutrosophic sets.The ability to account for components that are true,false or neither true nor false is useful in the resolution of real-life problems.However,simultaneous variations render neutrosophic sets unsuitable in specific circumstances.To enable the management of these sorts of issues,we combine the principle of multi-valued neutrosophic uncertain linguistic sets and complex fuzzy sets to develop the principle of multivalued complex neutrosophic uncertain linguistic sets.Multi-valued complex neutrosophic uncertain linguistic sets can contain grades of truth,abstinence,and falsity,and uncertain linguistic terms,which are expressed as complex numbers whose real and imaginary parts are limited to the unit interval.Some important Dombi laws are elaborated along with Bonferroni mean operators,which offer a flexible general structure with modifiable factors.Bonferroni means aggregation operators perform a significant role in conveying the magnitude level of options and characteristics.To determine relationships among any number of attributes,we develop multi-valued complex neutrosophic uncertain linguistic Dombi-normalized weighted Bonferroni mean operators and discuss their important properties with some special cases.By using these laws,we can deploy themulti-attribute decisionmaking(MADM)technique using the novel principle of multi-valued complex neutrosophic uncertain linguistic sets.To determine the power and flexibility of the elaborated approach,we resolve some numerical examples based on the proposed operator.Finally,the work is validated with the help of comparative analysis,a discussion of its advantages,and geometric expressions of the elaborated theories.展开更多
In this paper after analyzing the adaptation process of the proportionate normalized least mean square(PNLMS) algorithm, a statistical model is obtained to describe the convergence process of each adaptive filter coef...In this paper after analyzing the adaptation process of the proportionate normalized least mean square(PNLMS) algorithm, a statistical model is obtained to describe the convergence process of each adaptive filter coefcient. Inspired by this result, a modified PNLMS algorithm based on precise magnitude estimate is proposed. The simulation results indicate that in contrast to the traditional PNLMS algorithm, the proposed algorithm achieves faster convergence speed in the initial convergence state and lower misalignment in the stead stage with much less computational complexity.展开更多
The van Genuchten model is the most widely used soil water retention curve （SWRC） model. Two undisturbed soils （clay and loam） were used to evaluate the accuracy of the integral method to estimate van Genuchten mo...The van Genuchten model is the most widely used soil water retention curve （SWRC） model. Two undisturbed soils （clay and loam） were used to evaluate the accuracy of the integral method to estimate van Genuchten model parameters and to determine SWRCs of undisturbed soils. SWRCs calculated by the integral method were compared with those measured by a high speed centrifuge technique. The accuracy of the calculated results was evaluated graphically, as well as by root mean square error （RMSE）, normalized root mean square error （NRMSE） and Willmott＇s index of agreement （1）. The results obtained from the integral method were quite similar to those by the centrifuge technique. The RMSEs （4.61 ×10^-5 for Eum-Orthic Anthrosol and 2.74 × 10^-4 for Los-Orthic Entisol） and NRMSEs （1.56 × 10^-4 for Eum- Orthic Anthrosol and 1.45 ×10^-3 for Los-Orthic Entisol） were relatively small. The 1 values were 0.973 and 0.943 for Eum-Orthic Anthrosol and Los-Orthic Entisol, respectively, indicating a good agreement between the integral method values and the centrifuge values. Therefore, the integral method could be used to estimate SWRCs of undisturbed clay and loam soils.展开更多
Salinization is a gradual process that should be monitored.Modelling is a suitable alternative technique that saves time and cost for the field monitoring.But the performance of the models should be evaluated using th...Salinization is a gradual process that should be monitored.Modelling is a suitable alternative technique that saves time and cost for the field monitoring.But the performance of the models should be evaluated using the measured data.Therefore,the aim of this study was to evaluate and compare the SALTMED and HYDRUS-1D models using the measured soil water content,soil salinity and wheat yield data under different levels of saline irrigation water and groundwater depth.The field experiment was conducted in 2013 and in this research three controlled groundwater depths,i.e.,60(CD60),80(CD80)and 100(CD100)cm and two salinity levels of irrigation water,i.e.,4(EC4)and 8(EC8)dS/m were used in a complete randomized design with three replications.Soil water content and soil salinity were measured in soil profile and compared with the predicted values by the SALTMED and HYDRUS-1D models.Calibrations of the SALTMED and HYDRUS-1D models were carried out using the measured data under EC4-CD100 treatment and the data of the other treatments were used for validation.The statistical parameters including normalized root mean square error(NRMSE)and degree of agreement(d)showed that the values for predicting soil water content and soil salinity were more accurate in the HYDRUS-1D model than in the SALTMED model.The NRMSE and d values of the HYDRUS-1D model were 9.6%and 0.64 for the predicted soil water content and 6.2%and 0.98 for the predicted soil salinity,respectively.These indices of the SALTMED model were 10.6%and 0.81 for the predicted soil water content and 11.0%and 0.97 for the predicted soil salinity,respectively.According to the NRMSE and d values for the predicted wheat yield(9.8%and 0.91,respectively)and dry matter(2.9%and 0.99,respectively),we concluded that the SALTMED model predicted the wheat yield and dry matter accurately.展开更多
This paper investigates Carrier Frequency Offset (CFO) estimation in the uplink of the Orthogonal Frequency-Division Multiple Access (OFDMA) systems with the interleaved subcarrier assignment. CFOs between the transmi...This paper investigates Carrier Frequency Offset (CFO) estimation in the uplink of the Orthogonal Frequency-Division Multiple Access (OFDMA) systems with the interleaved subcarrier assignment. CFOs between the transmitters and the uplink receiver will destroy orthogonality among different subcarriers, hence resulting in inter-carrier interference and multiuser interference. A two-stage frequency offset estimation algorithm based on subspace processing is proposed. The main advantage of the proposed method is that it can obtain the CFOs of all users simultaneously using only one OFDMA block. Compared with the previously known methods, it not only has a relatively low implementation complexity but is also suitable for random subchannel assignment.展开更多
Joint location and scale models of the skew-normal distribution provide useful ex- tension for joint mean and variance models of the normal distribution when the data set under consideration involves asymmetric outcom...Joint location and scale models of the skew-normal distribution provide useful ex- tension for joint mean and variance models of the normal distribution when the data set under consideration involves asymmetric outcomes. This paper focuses on the maximum likelihood estimation of joint location and scale models of the skew-normal distribution. The proposed procedure can simultaneously estimate parameters in the location model and the scale model. Simulation studies and a real example are used to illustrate the proposed methodologies.展开更多
Using the linear approximation method, this paper studies the statistical property of a single-mode laser driven by both coloured pump noise with signal modulation and the quantum noise with cross-correlation between ...Using the linear approximation method, this paper studies the statistical property of a single-mode laser driven by both coloured pump noise with signal modulation and the quantum noise with cross-correlation between its real and imaginary parts, and calculates the steady-state mean normalized intensity fluctuation and intensity correlation time. It analyses the influences of the modulation signal, the net gain coefficient, the noise and its correlation form on the statistical fluctuation of the laser system respectively. It is found that the coloured pump noise modulated by the signal has a great suppressing action on the statistical fluctuation of the laser system; the pump noise self-correlation time and the specific frequency of modulation signal have the result that the statistical fluctuation tends to zero. Furthermore, the ＇colour＇ correlation of pump noise has much influences on the statistical fluctuation of the laser system. Increasing the intensity of pump noise will augment the statistical fluctuation of the laser system, but the intensity of quantum noise and the coefficient of cross-correlation between its real and imaginary parts have less influence on the statistical fluctuation of the laser system. Therefore, from the conclusions of this paper the statistical property can be known and a theoretical basis for steady operation and output of the laser system can be provided.展开更多
Some channel compensation techniques integrated into front-end of speech recognizer for improving channel robustness are described. These techniques include cepstral mean normalization, rasta processing and blind equa...Some channel compensation techniques integrated into front-end of speech recognizer for improving channel robustness are described. These techniques include cepstral mean normalization, rasta processing and blind equalization. Two standard channel frequency characteristics, G.712 and MIRS, are introduced as channel distortion references and a mandarin digit string recognition task is performed for evaluating and comparing the performance of these different methods. The recognition results show that in G.712 case blind equalization can achieve the best recognition performance while cepstral mean normalization outperforms the other methods in MIRS case which is capable of reaching a word error rate of 3.96%.展开更多
On the basis of calculating the steady-state mean normalized intensity fluctuation of a signal-mode laser system driven by both colored pump noise with signal modulation and the quantum noise with cross-correlation be...On the basis of calculating the steady-state mean normalized intensity fluctuation of a signal-mode laser system driven by both colored pump noise with signal modulation and the quantum noise with cross-correlation between its real and imaginary parts, we analyze the influence of modulation signal, noise, and its correlation form on the statistical fluctuation of the laser system. We have found that when the amplitude of modulation signal weakens and its frequency quickens, the statistical fluctuation will reduce rapidly. The by reducing the intensity of pump noise and quantum noise. statistical fluctuation of the laser system can be restrained Moreover, with prolonging of colored cross-correlation time, the statistical fluctuation of laser system experiences a repeated changing process, that is, from decreasing to augmenting, then to decreasing, and finally to augmenting again. With the decreasing of the value of cross-correlation coe~cient, the statistical fluctuation will decrease too. When the cross-correlation form between the real part and imaginary part of quantum noise is zero correlation, the statistical fluctuation of laser system has a minimum. Compared with the influence of intensity of pump noise, the influence of intensity of quantum noise on the statistical fluctuation is smaller.展开更多
Currently,the growth of micro and nano(very large scale integration-ultra large-scale integration)electronics technology has greatly impacted biomedical signal processing devices.These high-speed micro and nano techno...Currently,the growth of micro and nano(very large scale integration-ultra large-scale integration)electronics technology has greatly impacted biomedical signal processing devices.These high-speed micro and nano technology devices are very reliable despite their capacity to operate at tremendous speed,and can be designed to consume less power in minimum response time,which is particularly useful in biomedical products.The rapid technological scaling of the metal-oxide-semi-conductor(MOS)devices aids in mapping multiple applications for a specific purpose on a single chip which motivates us to design a sophisticated,small and reliable application specific integrated circuit(ASIC)chip for future real time medical signal separation and processing(digital stetho-scopes and digital microelectromechanical systems(MEMS)microphone).In this paper,ASIC level implementation of the adaptive line enhancer design using adaptive filtering algorithms(least mean square(LMS)and normalized least mean square(NLMS))integrated design is used to separate the real-time auscultation sound signals effectively.Adaptive line enhancer(ALE)design is imple-mented in Verilog hardware description language(HDL)language to obtain both the network and adaptive algorithm in cadence Taiwan Semiconductor Manufacturing Company(TSMC)90 nm standard cell library environment for ASIC level implementation.Native compiled simulator(NC)sim and RC lab were used for functional verification and design constraints and the physical design is implemented in Encounter to obtain the Geometric Data Stream(GDS II).In this architecture,the area occupied is 0.08 mm,the total power consumed is 5.05 mW and the computation time of the proposed system is 0.82μs for LMS design and the area occupied is 0.14 mm,the total power consumed is 4.54 mW and the computation time of the proposed system is 0.03μs for NLMS design that will pave a better way in future electronic stethoscope design.展开更多
In this paper,a general scheme in digital self-interference cancellation at baseband for zero-IF full-duplex transceivers is presented. We model the self-interference signals specifically with only the nonlinear disto...In this paper,a general scheme in digital self-interference cancellation at baseband for zero-IF full-duplex transceivers is presented. We model the self-interference signals specifically with only the nonlinear distortion signals falling in receiving band considered. A joint estimation algorithm is proposed for compensating the time delay and frequency offset taking into account the IQ amplitude and phase imbalances from mixers. The memory effect and nonlinear distortion are adaptively estimated by the de-correlated normalized least mean square(DNLMS) algorithm. Numerical simulation results demonstrate that the proposed self-interference cancellation scheme can efficiently compensate the self-interference and outperform the existing traditional solutions.展开更多
Based on daily mean temperature records from 1961 to 2007 at 20 meteorological sites in Southwest Yunnan, and the surface temperature simulated by IPCC AR4 Climate Models, a quantitative examination was undertaken int...Based on daily mean temperature records from 1961 to 2007 at 20 meteorological sites in Southwest Yunnan, and the surface temperature simulated by IPCC AR4 Climate Models, a quantitative examination was undertaken into the characteristics of multi-timescale temperature （AMT, DMT and WMT） variation in Southwest Yunnan. The simulation abilities of the models were also evaluated with the normalized root mean square error （NRMSE） and Mann-Kendal test statistic methods. Temperatures show remarkable increasing trend from 1961 to 2007, with the Mann-Kendall test statistic passing 95% confidence verification. The result of the NRMSE analysis shows that the simulated temperature anomaly variations are more similar to observed ones especially for AMT and DMT, and the projected result （anomalies） of IPCC AR4 climate models can be used for predicting the trends in multi-timescale temperature variation in Southwest Yunnan in the next 40 years under the three emission scenarios, which has better simulating effect on AMT and DMT than WMT. Over the next 40 years the temperature will continue to rise, with annual mean temperature showing a more remarkable rising trend than that of the dry and wet seasons. Temperature anomalies exhibit different increasing rates under different emission scenarios： During the 2020s the rising rates of multi-timescale temperature anomalies in a high greenhouse gases emissions scenario （SRESA2） are smaller than those under a low emission scenario （SRESB1）. Except that, the rate of increase in temperature anomalies are the highest in the intermediate emissions scenario （SRESA1B）, followed by those in SRESA2, and those in low emissions scenario （SRESB1） are the lowest. The reason of different simulating effects on WMT from AMT and DMT was also discussed.展开更多
Automobile companies that spend billions of dollars annually towards warranty cost, give high priority to warranty reduction programs. Forecasting of automobile warranty performance plays an important role towards the...Automobile companies that spend billions of dollars annually towards warranty cost, give high priority to warranty reduction programs. Forecasting of automobile warranty performance plays an important role towards these efforts. The forecasting process involves prediction of not only the specific months-in-service (MIS) warranty performance at certain future time, but also at future MIS values. However, 'maturing data' (also called warranty growth) phenomena that causes warranty performance at specific MIS values to change with time, makes such a forecasting task challenging. Although warranty forecasting methods such as log-log plots and dynamic linear models appear in literature, there is a need for applications addressing the well recognized issue of ‘maturing data’. In this paper we use an artificial neural network for the forecasting of warranty performance in presence of ‘maturing data’ phenomena. The network parameters are optimized by minimizing the training and testing errors using response surface methodology. This application shows the effectiveness of neural networks in the forecasting of automobile warranty performance in the presence of the ‘maturing data’ phenomena.展开更多
Distributed statistical inferences have attracted more and more attention in recent years with the emergence of massive data.We are grateful to the authors for the excellent review of the litera-ture in this active ar...Distributed statistical inferences have attracted more and more attention in recent years with the emergence of massive data.We are grateful to the authors for the excellent review of the litera-ture in this active area.Besides the progress mentioned by the authors,we would like to discuss some additional development in this interesting area.Specifically,we focus on the balance of communication cost and the statistical efficiency of divide-and-conquer(DC)type estimators in linear discriminant analysis and hypothesis testing.It is seen that the DC approach has different behaviours in these problems,which is different from that in estimation problems.Furthermore,we discuss some issues on the statistical inferences under restricted communication budgets.展开更多
文摘Although fuzzy set concepts have evolved,neutrosophic sets are attractingmore attention due to the greater power of the structure of neutrosophic sets.The ability to account for components that are true,false or neither true nor false is useful in the resolution of real-life problems.However,simultaneous variations render neutrosophic sets unsuitable in specific circumstances.To enable the management of these sorts of issues,we combine the principle of multi-valued neutrosophic uncertain linguistic sets and complex fuzzy sets to develop the principle of multivalued complex neutrosophic uncertain linguistic sets.Multi-valued complex neutrosophic uncertain linguistic sets can contain grades of truth,abstinence,and falsity,and uncertain linguistic terms,which are expressed as complex numbers whose real and imaginary parts are limited to the unit interval.Some important Dombi laws are elaborated along with Bonferroni mean operators,which offer a flexible general structure with modifiable factors.Bonferroni means aggregation operators perform a significant role in conveying the magnitude level of options and characteristics.To determine relationships among any number of attributes,we develop multi-valued complex neutrosophic uncertain linguistic Dombi-normalized weighted Bonferroni mean operators and discuss their important properties with some special cases.By using these laws,we can deploy themulti-attribute decisionmaking(MADM)technique using the novel principle of multi-valued complex neutrosophic uncertain linguistic sets.To determine the power and flexibility of the elaborated approach,we resolve some numerical examples based on the proposed operator.Finally,the work is validated with the help of comparative analysis,a discussion of its advantages,and geometric expressions of the elaborated theories.
文摘In this paper after analyzing the adaptation process of the proportionate normalized least mean square(PNLMS) algorithm, a statistical model is obtained to describe the convergence process of each adaptive filter coefcient. Inspired by this result, a modified PNLMS algorithm based on precise magnitude estimate is proposed. The simulation results indicate that in contrast to the traditional PNLMS algorithm, the proposed algorithm achieves faster convergence speed in the initial convergence state and lower misalignment in the stead stage with much less computational complexity.
基金Project supported by the International Partnership Program for Creative Research Teams of the Chinese Academy of Sciences (CAS) & the State Administration of Foreign Experts Affairs (SAFEA), China, and the Hundreds-Talent Program of the Chinese Academy of Sciences, China (No. 90502006)
文摘The van Genuchten model is the most widely used soil water retention curve （SWRC） model. Two undisturbed soils （clay and loam） were used to evaluate the accuracy of the integral method to estimate van Genuchten model parameters and to determine SWRCs of undisturbed soils. SWRCs calculated by the integral method were compared with those measured by a high speed centrifuge technique. The accuracy of the calculated results was evaluated graphically, as well as by root mean square error （RMSE）, normalized root mean square error （NRMSE） and Willmott＇s index of agreement （1）. The results obtained from the integral method were quite similar to those by the centrifuge technique. The RMSEs （4.61 ×10^-5 for Eum-Orthic Anthrosol and 2.74 × 10^-4 for Los-Orthic Entisol） and NRMSEs （1.56 × 10^-4 for Eum- Orthic Anthrosol and 1.45 ×10^-3 for Los-Orthic Entisol） were relatively small. The 1 values were 0.973 and 0.943 for Eum-Orthic Anthrosol and Los-Orthic Entisol, respectively, indicating a good agreement between the integral method values and the centrifuge values. Therefore, the integral method could be used to estimate SWRCs of undisturbed clay and loam soils.
基金This research was supported in part by the Project of the Shiraz University Research Council,Iran(94GCU5M1923)。
文摘Salinization is a gradual process that should be monitored.Modelling is a suitable alternative technique that saves time and cost for the field monitoring.But the performance of the models should be evaluated using the measured data.Therefore,the aim of this study was to evaluate and compare the SALTMED and HYDRUS-1D models using the measured soil water content,soil salinity and wheat yield data under different levels of saline irrigation water and groundwater depth.The field experiment was conducted in 2013 and in this research three controlled groundwater depths,i.e.,60(CD60),80(CD80)and 100(CD100)cm and two salinity levels of irrigation water,i.e.,4(EC4)and 8(EC8)dS/m were used in a complete randomized design with three replications.Soil water content and soil salinity were measured in soil profile and compared with the predicted values by the SALTMED and HYDRUS-1D models.Calibrations of the SALTMED and HYDRUS-1D models were carried out using the measured data under EC4-CD100 treatment and the data of the other treatments were used for validation.The statistical parameters including normalized root mean square error(NRMSE)and degree of agreement(d)showed that the values for predicting soil water content and soil salinity were more accurate in the HYDRUS-1D model than in the SALTMED model.The NRMSE and d values of the HYDRUS-1D model were 9.6%and 0.64 for the predicted soil water content and 6.2%and 0.98 for the predicted soil salinity,respectively.These indices of the SALTMED model were 10.6%and 0.81 for the predicted soil water content and 11.0%and 0.97 for the predicted soil salinity,respectively.According to the NRMSE and d values for the predicted wheat yield(9.8%and 0.91,respectively)and dry matter(2.9%and 0.99,respectively),we concluded that the SALTMED model predicted the wheat yield and dry matter accurately.
基金the Specialized Research Fund for the Doctoral Program of Higher Education, China Ministry of Education (No.20030003039).
文摘This paper investigates Carrier Frequency Offset (CFO) estimation in the uplink of the Orthogonal Frequency-Division Multiple Access (OFDMA) systems with the interleaved subcarrier assignment. CFOs between the transmitters and the uplink receiver will destroy orthogonality among different subcarriers, hence resulting in inter-carrier interference and multiuser interference. A two-stage frequency offset estimation algorithm based on subspace processing is proposed. The main advantage of the proposed method is that it can obtain the CFOs of all users simultaneously using only one OFDMA block. Compared with the previously known methods, it not only has a relatively low implementation complexity but is also suitable for random subchannel assignment.
基金Supported by the National Natural Science Foundation of China(11261025,11201412)the Natural Science Foundation of Yunnan Province(2011FB016)the Program for Middle-aged Backbone Teacher,Yunnan University
文摘Joint location and scale models of the skew-normal distribution provide useful ex- tension for joint mean and variance models of the normal distribution when the data set under consideration involves asymmetric outcomes. This paper focuses on the maximum likelihood estimation of joint location and scale models of the skew-normal distribution. The proposed procedure can simultaneously estimate parameters in the location model and the scale model. Simulation studies and a real example are used to illustrate the proposed methodologies.
基金Project supported by the National Natural Science Foundation of China （Grant No 10275025） and Emphases Item of Education 0ffice of Hubei Province China （Grant Nos D200612001 and 2004X052）.
文摘Using the linear approximation method, this paper studies the statistical property of a single-mode laser driven by both coloured pump noise with signal modulation and the quantum noise with cross-correlation between its real and imaginary parts, and calculates the steady-state mean normalized intensity fluctuation and intensity correlation time. It analyses the influences of the modulation signal, the net gain coefficient, the noise and its correlation form on the statistical fluctuation of the laser system respectively. It is found that the coloured pump noise modulated by the signal has a great suppressing action on the statistical fluctuation of the laser system; the pump noise self-correlation time and the specific frequency of modulation signal have the result that the statistical fluctuation tends to zero. Furthermore, the ＇colour＇ correlation of pump noise has much influences on the statistical fluctuation of the laser system. Increasing the intensity of pump noise will augment the statistical fluctuation of the laser system, but the intensity of quantum noise and the coefficient of cross-correlation between its real and imaginary parts have less influence on the statistical fluctuation of the laser system. Therefore, from the conclusions of this paper the statistical property can be known and a theoretical basis for steady operation and output of the laser system can be provided.
文摘Some channel compensation techniques integrated into front-end of speech recognizer for improving channel robustness are described. These techniques include cepstral mean normalization, rasta processing and blind equalization. Two standard channel frequency characteristics, G.712 and MIRS, are introduced as channel distortion references and a mandarin digit string recognition task is performed for evaluating and comparing the performance of these different methods. The recognition results show that in G.712 case blind equalization can achieve the best recognition performance while cepstral mean normalization outperforms the other methods in MIRS case which is capable of reaching a word error rate of 3.96%.
基金The project supported by National Natural Science Foundation of China under Grant No. 10275025 and the Emphases Item of Education Department of Hubei Province under Grant No. 2004X052
文摘On the basis of calculating the steady-state mean normalized intensity fluctuation of a signal-mode laser system driven by both colored pump noise with signal modulation and the quantum noise with cross-correlation between its real and imaginary parts, we analyze the influence of modulation signal, noise, and its correlation form on the statistical fluctuation of the laser system. We have found that when the amplitude of modulation signal weakens and its frequency quickens, the statistical fluctuation will reduce rapidly. The by reducing the intensity of pump noise and quantum noise. statistical fluctuation of the laser system can be restrained Moreover, with prolonging of colored cross-correlation time, the statistical fluctuation of laser system experiences a repeated changing process, that is, from decreasing to augmenting, then to decreasing, and finally to augmenting again. With the decreasing of the value of cross-correlation coe~cient, the statistical fluctuation will decrease too. When the cross-correlation form between the real part and imaginary part of quantum noise is zero correlation, the statistical fluctuation of laser system has a minimum. Compared with the influence of intensity of pump noise, the influence of intensity of quantum noise on the statistical fluctuation is smaller.
文摘Currently,the growth of micro and nano(very large scale integration-ultra large-scale integration)electronics technology has greatly impacted biomedical signal processing devices.These high-speed micro and nano technology devices are very reliable despite their capacity to operate at tremendous speed,and can be designed to consume less power in minimum response time,which is particularly useful in biomedical products.The rapid technological scaling of the metal-oxide-semi-conductor(MOS)devices aids in mapping multiple applications for a specific purpose on a single chip which motivates us to design a sophisticated,small and reliable application specific integrated circuit(ASIC)chip for future real time medical signal separation and processing(digital stetho-scopes and digital microelectromechanical systems(MEMS)microphone).In this paper,ASIC level implementation of the adaptive line enhancer design using adaptive filtering algorithms(least mean square(LMS)and normalized least mean square(NLMS))integrated design is used to separate the real-time auscultation sound signals effectively.Adaptive line enhancer(ALE)design is imple-mented in Verilog hardware description language(HDL)language to obtain both the network and adaptive algorithm in cadence Taiwan Semiconductor Manufacturing Company(TSMC)90 nm standard cell library environment for ASIC level implementation.Native compiled simulator(NC)sim and RC lab were used for functional verification and design constraints and the physical design is implemented in Encounter to obtain the Geometric Data Stream(GDS II).In this architecture,the area occupied is 0.08 mm,the total power consumed is 5.05 mW and the computation time of the proposed system is 0.82μs for LMS design and the area occupied is 0.14 mm,the total power consumed is 4.54 mW and the computation time of the proposed system is 0.03μs for NLMS design that will pave a better way in future electronic stethoscope design.
基金supported in part by the National Natural Science Foundation of China(No.61601027)
文摘In this paper,a general scheme in digital self-interference cancellation at baseband for zero-IF full-duplex transceivers is presented. We model the self-interference signals specifically with only the nonlinear distortion signals falling in receiving band considered. A joint estimation algorithm is proposed for compensating the time delay and frequency offset taking into account the IQ amplitude and phase imbalances from mixers. The memory effect and nonlinear distortion are adaptively estimated by the de-correlated normalized least mean square(DNLMS) algorithm. Numerical simulation results demonstrate that the proposed self-interference cancellation scheme can efficiently compensate the self-interference and outperform the existing traditional solutions.
基金National Natural Science Foundation of China (40901050), National Basic Research Program of China (No. 2012CB955903)Scientific Research Fund Project of Yunnan Provincial Department of Education (No. 09Y0284, "Technology Research of Adaptation and Mitigation to Yunnan Climate Change")
文摘Based on daily mean temperature records from 1961 to 2007 at 20 meteorological sites in Southwest Yunnan, and the surface temperature simulated by IPCC AR4 Climate Models, a quantitative examination was undertaken into the characteristics of multi-timescale temperature （AMT, DMT and WMT） variation in Southwest Yunnan. The simulation abilities of the models were also evaluated with the normalized root mean square error （NRMSE） and Mann-Kendal test statistic methods. Temperatures show remarkable increasing trend from 1961 to 2007, with the Mann-Kendall test statistic passing 95% confidence verification. The result of the NRMSE analysis shows that the simulated temperature anomaly variations are more similar to observed ones especially for AMT and DMT, and the projected result （anomalies） of IPCC AR4 climate models can be used for predicting the trends in multi-timescale temperature variation in Southwest Yunnan in the next 40 years under the three emission scenarios, which has better simulating effect on AMT and DMT than WMT. Over the next 40 years the temperature will continue to rise, with annual mean temperature showing a more remarkable rising trend than that of the dry and wet seasons. Temperature anomalies exhibit different increasing rates under different emission scenarios： During the 2020s the rising rates of multi-timescale temperature anomalies in a high greenhouse gases emissions scenario （SRESA2） are smaller than those under a low emission scenario （SRESB1）. Except that, the rate of increase in temperature anomalies are the highest in the intermediate emissions scenario （SRESA1B）, followed by those in SRESA2, and those in low emissions scenario （SRESB1） are the lowest. The reason of different simulating effects on WMT from AMT and DMT was also discussed.
文摘Automobile companies that spend billions of dollars annually towards warranty cost, give high priority to warranty reduction programs. Forecasting of automobile warranty performance plays an important role towards these efforts. The forecasting process involves prediction of not only the specific months-in-service (MIS) warranty performance at certain future time, but also at future MIS values. However, 'maturing data' (also called warranty growth) phenomena that causes warranty performance at specific MIS values to change with time, makes such a forecasting task challenging. Although warranty forecasting methods such as log-log plots and dynamic linear models appear in literature, there is a need for applications addressing the well recognized issue of ‘maturing data’. In this paper we use an artificial neural network for the forecasting of warranty performance in presence of ‘maturing data’ phenomena. The network parameters are optimized by minimizing the training and testing errors using response surface methodology. This application shows the effectiveness of neural networks in the forecasting of automobile warranty performance in the presence of the ‘maturing data’ phenomena.
文摘Distributed statistical inferences have attracted more and more attention in recent years with the emergence of massive data.We are grateful to the authors for the excellent review of the litera-ture in this active area.Besides the progress mentioned by the authors,we would like to discuss some additional development in this interesting area.Specifically,we focus on the balance of communication cost and the statistical efficiency of divide-and-conquer(DC)type estimators in linear discriminant analysis and hypothesis testing.It is seen that the DC approach has different behaviours in these problems,which is different from that in estimation problems.Furthermore,we discuss some issues on the statistical inferences under restricted communication budgets.
