An analytical model of gate-all-around （GAA） silicon nanowire tunneling field effect transistors （NW-TFETs） is developted based on the surface potential solutions in the channel direction and considering the band ...An analytical model of gate-all-around （GAA） silicon nanowire tunneling field effect transistors （NW-TFETs） is developted based on the surface potential solutions in the channel direction and considering the band to band tunneling （BTBT） efficiency. The three-dimensional Poisson equation is solved to obtain the surface potential distributions in the partition regions along the channel direction for the NW-TFET, and a tunneling current model using Kane＇s expression is developed. The validity of the developed model is shown by the good agreement between the model predictions and the TCAD simulation results.展开更多
Automatic speech recognition (ASR) is vital for very low-resource languages for mitigating the extinction trouble. Chaha is one of the low-resource languages, which suffers from the problem of resource insufficiency a...Automatic speech recognition (ASR) is vital for very low-resource languages for mitigating the extinction trouble. Chaha is one of the low-resource languages, which suffers from the problem of resource insufficiency and some of its phonological, morphological, and orthographic features challenge the development and initiatives in the area of ASR. By considering these challenges, this study is the first endeavor, which analyzed the characteristics of the language, prepared speech corpus, and developed different ASR systems. A small 3-hour read speech corpus was prepared and transcribed. Different basic and rounded phone unit-based speech recognizers were explored using multilingual deep neural network (DNN) modeling methods. The experimental results demonstrated that all the basic phone and rounded phone unit-based multilingual models outperformed the corresponding unilingual models with the relative performance improvements of 5.47% to 19.87% and 5.74% to 16.77%, respectively. The rounded phone unit-based multilingual models outperformed the equivalent basic phone unit-based models with relative performance improvements of 0.95% to 4.98%. Overall, we discovered that multilingual DNN modeling methods are profoundly effective to develop Chaha speech recognizers. Both the basic and rounded phone acoustic units are convenient to build Chaha ASR system. However, the rounded phone unit-based models are superior in performance and faster in recognition speed over the corresponding basic phone unit-based models. Hence, the rounded phone units are the most suitable acoustic units to develop Chaha ASR systems.展开更多
Automatic target recognition （ATR） is an important issue for military applications, the topic of the ATR system belongs to the field of pattern recognition and classification. In the paper, we present an approach fo...Automatic target recognition （ATR） is an important issue for military applications, the topic of the ATR system belongs to the field of pattern recognition and classification. In the paper, we present an approach for building an ATR system with improved artificial neural network to recog- nize and classify the typical targets in the battle field. The invariant features of Hu invariant moments and roundness were selected to be the inputs of the neural network because they have the invari- ances of rotation, translation and scaling. The pictures of the targets are generated by the 3-D mod- els to improve the recognition rate because it is necessary to provide enough pictures for training the artificial neural network. The simulations prove that the approach can be implement ed in the ATR system and it has a high recognition rate and can be applied in real time.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.61274096,61204043,61306042,61306045,and 61306132)the Guangdong Natural Science Foundation,China(Grant Nos.S2012010010533 and S2013040016878)+2 种基金the Shenzhen Science&Technology Foundation,China(Grant No.ZDSY20120618161735041)the Fundamental Research Project of the Shenzhen Science&Technology Foundation,China(Grant Nos.JCYJ20120618162600041,JCYJ20120618162526384,JCYJ20130402164725025,and JCYJ20120618162946025)the International Collaboration Project of the Shenzhen Science&Technology Foundation,China(Grant Nos.GJHZ20120618162120759,GJHZ20130417170946221,GJHZ20130417170908049,and GJHZ20120615142829482)
文摘An analytical model of gate-all-around （GAA） silicon nanowire tunneling field effect transistors （NW-TFETs） is developted based on the surface potential solutions in the channel direction and considering the band to band tunneling （BTBT） efficiency. The three-dimensional Poisson equation is solved to obtain the surface potential distributions in the partition regions along the channel direction for the NW-TFET, and a tunneling current model using Kane＇s expression is developed. The validity of the developed model is shown by the good agreement between the model predictions and the TCAD simulation results.
文摘Automatic speech recognition (ASR) is vital for very low-resource languages for mitigating the extinction trouble. Chaha is one of the low-resource languages, which suffers from the problem of resource insufficiency and some of its phonological, morphological, and orthographic features challenge the development and initiatives in the area of ASR. By considering these challenges, this study is the first endeavor, which analyzed the characteristics of the language, prepared speech corpus, and developed different ASR systems. A small 3-hour read speech corpus was prepared and transcribed. Different basic and rounded phone unit-based speech recognizers were explored using multilingual deep neural network (DNN) modeling methods. The experimental results demonstrated that all the basic phone and rounded phone unit-based multilingual models outperformed the corresponding unilingual models with the relative performance improvements of 5.47% to 19.87% and 5.74% to 16.77%, respectively. The rounded phone unit-based multilingual models outperformed the equivalent basic phone unit-based models with relative performance improvements of 0.95% to 4.98%. Overall, we discovered that multilingual DNN modeling methods are profoundly effective to develop Chaha speech recognizers. Both the basic and rounded phone acoustic units are convenient to build Chaha ASR system. However, the rounded phone unit-based models are superior in performance and faster in recognition speed over the corresponding basic phone unit-based models. Hence, the rounded phone units are the most suitable acoustic units to develop Chaha ASR systems.
基金Supported by the Ministerial Level Advanced Research Foundation(9140A01010411BQ01)the National Twelfth Five-Year Project(40405050303)
文摘Automatic target recognition （ATR） is an important issue for military applications, the topic of the ATR system belongs to the field of pattern recognition and classification. In the paper, we present an approach for building an ATR system with improved artificial neural network to recog- nize and classify the typical targets in the battle field. The invariant features of Hu invariant moments and roundness were selected to be the inputs of the neural network because they have the invari- ances of rotation, translation and scaling. The pictures of the targets are generated by the 3-D mod- els to improve the recognition rate because it is necessary to provide enough pictures for training the artificial neural network. The simulations prove that the approach can be implement ed in the ATR system and it has a high recognition rate and can be applied in real time.
