This paper presented an approach to hide secret speech information in code excited linear prediction (CELP)-based speech coding scheme by adopting the analysis-by-synthesis (ABS)-based algorithm of speech information ...This paper presented an approach to hide secret speech information in code excited linear prediction (CELP)-based speech coding scheme by adopting the analysis-by-synthesis (ABS)-based algorithm of speech information hiding and extracting for the purpose of secure speech communication. The secret speech is coded in 2.4 Kb/s mixed excitation linear prediction (MELP), which is embedded in CELP type public speech. The ABS algorithm adopts speech synthesizer in speech coder. Speech embedding and coding are synchronous, i.e. a fusion of speech information data of public and secret. The experiment of embedding 2.4 Kb/s MELP secret speech in G.728 scheme coded public speech transmitted via public switched telephone network (PSTN) shows that the proposed approach satisfies the requirements of information hiding, meets the secure communication speech quality constraints, and achieves high hiding capacity of average 3.2 Kb/s with an excellent speech quality and complicating speakers’ recognition.展开更多
This paper refers to the CNOP-related algorithms and formulates the practical method and forecast techniques of extracting predictable components in a numerical model for predictable components on extended-range scale...This paper refers to the CNOP-related algorithms and formulates the practical method and forecast techniques of extracting predictable components in a numerical model for predictable components on extended-range scales.Model variables are divided into predictable components and unpredictable chaotic components from the angle of model prediction error growth.The predictable components are defined as those with a slow error growth at a given range.A targeted numerical model for predictable components is established based on the operational dynamical extended-range forecast(DERF)model of the National Climate Center.At the same time,useful information in historical data are combined to find the fields for predictable components in the numerical model that are similar to those for the predictable components in historical data,reducing the variable dimensions in a similar judgment process and further correcting prediction errors of predictable components.Historical data is used to obtain the expected value and variance of the chaotic components through the ensemble forecast method.The numerical experiment results show that this method can effectively improve the forecast skill of the atmospheric circulation field in the 10–30 days extended-range numerical model and has good prospects for operational applications.展开更多
Although extended-range forecasting has exceeded the limit of daily predictability of weather,there are still partially predictable characteristics of meteorological fields in such forecasts.A targeted forecast scheme...Although extended-range forecasting has exceeded the limit of daily predictability of weather,there are still partially predictable characteristics of meteorological fields in such forecasts.A targeted forecast scheme and strategy for extended-range predictable components is proposed.Based on chaotic characteristics of the atmosphere,predictable components and unpredictable random components are separated by using the standpoint of error growth in a numerical model.The predictable components are defined as those with slow error growth at a given range,which are not sensitive to small errors in initial conditions. A numerical model for predictable components(NMPC)is established,by filtering random components with poor predictability.The aim is to maintain predictable components and avoid the influence of rapidly growing forecast errors on small scales. Meanwhile,the analogue-dynamical approach(ADA)is used to correct forecast errors of predictable components,to decrease model error and statistically take into account the influence of random components.The scheme is applied to operational dynamical extended-range forecast(DERF)model of the National Climate Center of China Meteorological Administration (NCC/CMA).Prediction results show that the scheme can improve forecast skill of predictable components to some extent, especially in high predictability regions.Forecast skill at zonal wave zero is improved more than for ultra-long waves and synoptic-scale waves.Results show good agreement with predictability of spatial scale.As a result,the scheme can reduce forecast errors and improve forecast skill,which favors operational use.展开更多
文摘This paper presented an approach to hide secret speech information in code excited linear prediction (CELP)-based speech coding scheme by adopting the analysis-by-synthesis (ABS)-based algorithm of speech information hiding and extracting for the purpose of secure speech communication. The secret speech is coded in 2.4 Kb/s mixed excitation linear prediction (MELP), which is embedded in CELP type public speech. The ABS algorithm adopts speech synthesizer in speech coder. Speech embedding and coding are synchronous, i.e. a fusion of speech information data of public and secret. The experiment of embedding 2.4 Kb/s MELP secret speech in G.728 scheme coded public speech transmitted via public switched telephone network (PSTN) shows that the proposed approach satisfies the requirements of information hiding, meets the secure communication speech quality constraints, and achieves high hiding capacity of average 3.2 Kb/s with an excellent speech quality and complicating speakers’ recognition.
基金supported by the National Natural Science Foundation of China (Grant Nos. 40930952, 41105055)Global Change Study of Major National Scientific Research Plan of China (Grant No. 2012CB955902)Meteorological Special Project of China (Grant Nos. GYHY201106016, GYHY201106015)
文摘This paper refers to the CNOP-related algorithms and formulates the practical method and forecast techniques of extracting predictable components in a numerical model for predictable components on extended-range scales.Model variables are divided into predictable components and unpredictable chaotic components from the angle of model prediction error growth.The predictable components are defined as those with a slow error growth at a given range.A targeted numerical model for predictable components is established based on the operational dynamical extended-range forecast(DERF)model of the National Climate Center.At the same time,useful information in historical data are combined to find the fields for predictable components in the numerical model that are similar to those for the predictable components in historical data,reducing the variable dimensions in a similar judgment process and further correcting prediction errors of predictable components.Historical data is used to obtain the expected value and variance of the chaotic components through the ensemble forecast method.The numerical experiment results show that this method can effectively improve the forecast skill of the atmospheric circulation field in the 10–30 days extended-range numerical model and has good prospects for operational applications.
基金supported by National Natural Science Foundation of China (Grant Nos.41105070,40930952 and 41005041)State Key Program of Science and Technology of China(Grant No.2009BAC51B04)Meteorological Special Project of China(Grant No.GYHY 201106016)
文摘Although extended-range forecasting has exceeded the limit of daily predictability of weather,there are still partially predictable characteristics of meteorological fields in such forecasts.A targeted forecast scheme and strategy for extended-range predictable components is proposed.Based on chaotic characteristics of the atmosphere,predictable components and unpredictable random components are separated by using the standpoint of error growth in a numerical model.The predictable components are defined as those with slow error growth at a given range,which are not sensitive to small errors in initial conditions. A numerical model for predictable components(NMPC)is established,by filtering random components with poor predictability.The aim is to maintain predictable components and avoid the influence of rapidly growing forecast errors on small scales. Meanwhile,the analogue-dynamical approach(ADA)is used to correct forecast errors of predictable components,to decrease model error and statistically take into account the influence of random components.The scheme is applied to operational dynamical extended-range forecast(DERF)model of the National Climate Center of China Meteorological Administration (NCC/CMA).Prediction results show that the scheme can improve forecast skill of predictable components to some extent, especially in high predictability regions.Forecast skill at zonal wave zero is improved more than for ultra-long waves and synoptic-scale waves.Results show good agreement with predictability of spatial scale.As a result,the scheme can reduce forecast errors and improve forecast skill,which favors operational use.
