When checking the ice shape calculation software,its accuracy is judged based on the proximity between the calculated ice shape and the typical test ice shape.Therefore,determining the typical test ice shape becomes t...When checking the ice shape calculation software,its accuracy is judged based on the proximity between the calculated ice shape and the typical test ice shape.Therefore,determining the typical test ice shape becomes the key task of the icing wind tunnel tests.In the icing wind tunnel test of the tail wing model of a large amphibious aircraft,in order to obtain accurate typical test ice shape,the Romer Absolute Scanner is used to obtain the 3D point cloud data of the ice shape on the tail wing model.Then,the batch-learning self-organizing map(BLSOM)neural network is used to obtain the 2D average ice shape along the model direction based on the 3D point cloud data of the ice shape,while its tolerance band is calculated using the probabilistic statistical method.The results show that the combination of 2D average ice shape and its tolerance band can represent the 3D characteristics of the test ice shape effectively,which can be used as the typical test ice shape for comparative analysis with the calculated ice shape.展开更多
A methodology is presented whereby a neural network is used to learn the inverse kinematic relationships of the position and orientation of a six joint manipulator. The arm solution for the orientation of a manipulato...A methodology is presented whereby a neural network is used to learn the inverse kinematic relationships of the position and orientation of a six joint manipulator. The arm solution for the orientation of a manipulator using a self organizing neural net is studied in this paper. A new training model of the self organizing neural network is proposed by thoroughly studying Martinetz, Ritter and Schulten′s self organizing neural network based on Kohonen′s self organizing mapping algorithm using a Widrow Hoff type error correction rule and closely combining the characters of the inverse kinematic relationship for a robot arm. The computer simulation results for a PUMA 560 robot show that the proposed method has a significant improvement over other methods documented in the references in self organizing capability and precision by training process.展开更多
In this paper, we propose a novel block cryptographic scheme based on a spatiotemporal chaotic system and a chaotic neural network （CNN）. The employed CNN comprises a 4-neuron layer called a chaotic neuron layer （...In this paper, we propose a novel block cryptographic scheme based on a spatiotemporal chaotic system and a chaotic neural network （CNN）. The employed CNN comprises a 4-neuron layer called a chaotic neuron layer （CNL）, where the spatiotemporal chaotic system participates in generating its weight matrix and other parameters. The spatiotemporal chaotic system used in our scheme is the typical coupled map lattice （CML）, which can be easily implemented in parallel by hard- ware. A 160-bit-long binary sequence is used to generate the initial conditions of the CML. The decryption process is symmetric relative to the encryption process. Theoretical analysis and experimental results prove that the block cryptosys- tem is secure and practical, and suitable for image encryption.展开更多
We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural net...We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks.展开更多
In this paper we discuss neural network-based matrix effect correction in energy dispersive X-ray fluorescence (EDXRF) analysis,with detailed algorithm to classify the samples.The method can correct the matrix effect ...In this paper we discuss neural network-based matrix effect correction in energy dispersive X-ray fluorescence (EDXRF) analysis,with detailed algorithm to classify the samples.The method can correct the matrix effect effectively through classifying the samples automatically,and influence of X-ray absorption and enhancement by major elements of the samples is reduced.Experiments for the complex matrix effect correction in EDXRF analysis of samples in Pangang showed improved accuracy of the elemental analysis result.展开更多
Memristive neural network has attracted tremendous attention since the memristor array can perform parallel multiplyaccumulate calculation(MAC)operations and memory-computation operations as compared with digital CMOS...Memristive neural network has attracted tremendous attention since the memristor array can perform parallel multiplyaccumulate calculation(MAC)operations and memory-computation operations as compared with digital CMOS hardware systems.However,owing to the variability of the memristor,the implementation of high-precision neural network in memristive computation units is still difficult.Existing learning algorithms for memristive artificial neural network(ANN)is unable to achieve the performance comparable to high-precision by using CMOS-based system.Here,we propose an algorithm based on off-chip learning for memristive ANN in low precision.Training the ANN in the high-precision in digital CPUs and then quantifying the weight of the network to low precision,the quantified weights are mapped to the memristor arrays based on VTEAM model through using the pulse coding weight-mapping rule.In this work,we execute the inference of trained 5-layers convolution neural network on the memristor arrays and achieve an accuracy close to the inference in the case of high precision(64-bit).Compared with other algorithms-based off-chip learning,the algorithm proposed in the present study can easily implement the mapping process and less influence of the device variability.Our result provides an effective approach to implementing the ANN on the memristive hardware platform.展开更多
南水入冀新水情下,百泉泉域地下水环境发生改变,岩溶地下水地球化学过程有待查明。综合利用数值模拟、机器学习(自组织聚类)和同位素(δD和δ^(18)O)等方法系统揭示了矿业活动与南水入冀下百泉泉域岩溶地下水地球化学过程,并基于熵变权...南水入冀新水情下,百泉泉域地下水环境发生改变,岩溶地下水地球化学过程有待查明。综合利用数值模拟、机器学习(自组织聚类)和同位素(δD和δ^(18)O)等方法系统揭示了矿业活动与南水入冀下百泉泉域岩溶地下水地球化学过程,并基于熵变权水质指数(Entropy-weighted water quality index,EWQI)进行了水质分级评价。南水入冀后,百泉泉域岩溶地下水位整体抬升。时间上,呈现出既有年际动态变化又有年内季节变化特征。空间上,补给区表现为剧变型,而径流、排泄区呈缓变型。地下水降落漏斗主要分布在泉域东南部的煤、铁矿密集区。泉域岩溶地下水呈弱碱性,水化学类型以Ca-HCO_(3)型和Ca-SO_(4)型为主导。主要阴阳离子质量浓度遵循ρ(HCO_(3)^(-))>ρ(SO_(4)^(2-))>ρ(Cl^(-))和ρ(Ca^(2+))>ρ(Mg^(2+))>ρ(Na^(+))>ρ(K^(+))的顺序。各离子沿着径流路径呈现出逐渐增大的空间分布特征。岩溶地下水化学成分主要受岩石(方解石、白云石和石膏)风化溶解和反向阳离子交换作用主导。人为活动对泉域岩溶地下水系统中的SO_(4)^(2-)和NO_(3)^(-)质量浓度有一定程度影响。岩溶地下水来源于大气降水,并且在入渗前发生了二次蒸发作用,氘盈余值在径流过程中有所降低。水质评价结果表明,岩溶地下水质量整体优于第四系地下水,分别有50%的岩溶水和37.5%的第四系水样满足饮用目的。TDS、ρ(SO_(4)^(2-))和ρ(NO_(3)^(-))是影响泉域地下水水质的关键指标。引起泉域岩溶地下水系统水质恶化的潜在人类活动主要包括矿山排水、农业灌溉和城市污水排放。通过水质分级评价,提出了泉域地下水环境保护措施。研究结果将有助于为百泉泉域岩溶地下水资源的供水安全和地下水环境保护治理提供参考。展开更多
基金supported by the AG600 project of AVIC General Huanan Aircraft Industry Co.,Ltd.
文摘When checking the ice shape calculation software,its accuracy is judged based on the proximity between the calculated ice shape and the typical test ice shape.Therefore,determining the typical test ice shape becomes the key task of the icing wind tunnel tests.In the icing wind tunnel test of the tail wing model of a large amphibious aircraft,in order to obtain accurate typical test ice shape,the Romer Absolute Scanner is used to obtain the 3D point cloud data of the ice shape on the tail wing model.Then,the batch-learning self-organizing map(BLSOM)neural network is used to obtain the 2D average ice shape along the model direction based on the 3D point cloud data of the ice shape,while its tolerance band is calculated using the probabilistic statistical method.The results show that the combination of 2D average ice shape and its tolerance band can represent the 3D characteristics of the test ice shape effectively,which can be used as the typical test ice shape for comparative analysis with the calculated ice shape.
文摘A methodology is presented whereby a neural network is used to learn the inverse kinematic relationships of the position and orientation of a six joint manipulator. The arm solution for the orientation of a manipulator using a self organizing neural net is studied in this paper. A new training model of the self organizing neural network is proposed by thoroughly studying Martinetz, Ritter and Schulten′s self organizing neural network based on Kohonen′s self organizing mapping algorithm using a Widrow Hoff type error correction rule and closely combining the characters of the inverse kinematic relationship for a robot arm. The computer simulation results for a PUMA 560 robot show that the proposed method has a significant improvement over other methods documented in the references in self organizing capability and precision by training process.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 61173183, 60973152, and 60573172)the Doctoral Program Foundation of Institution of Higher Education of China (Grant No. 20070141014)+2 种基金the Program for Excellent Talents in Universities of Liaoning Province, China (Grant No. LR2012003)the Natural Science Foundation of Liaoning Province, China (Grant No. 20082165)the Fundamental Research Funds for the Central Universities of China (Grant No. DUT12JB06)
文摘In this paper, we propose a novel block cryptographic scheme based on a spatiotemporal chaotic system and a chaotic neural network （CNN）. The employed CNN comprises a 4-neuron layer called a chaotic neuron layer （CNL）, where the spatiotemporal chaotic system participates in generating its weight matrix and other parameters. The spatiotemporal chaotic system used in our scheme is the typical coupled map lattice （CML）, which can be easily implemented in parallel by hard- ware. A 160-bit-long binary sequence is used to generate the initial conditions of the CML. The decryption process is symmetric relative to the encryption process. Theoretical analysis and experimental results prove that the block cryptosys- tem is secure and practical, and suitable for image encryption.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 61173183,60973152,and 60573172)the Superior University Doctor Subject Special Scientific Research Foundation of China (Grant No. 20070141014)the Natural Science Foundation of Liaoning Province,China (Grant No. 20082165)
文摘We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks.
基金supported by the National Natural Science Foundation of China (No.40574059)the Ministry of Education (No.NCET-04-0904)
文摘In this paper we discuss neural network-based matrix effect correction in energy dispersive X-ray fluorescence (EDXRF) analysis,with detailed algorithm to classify the samples.The method can correct the matrix effect effectively through classifying the samples automatically,and influence of X-ray absorption and enhancement by major elements of the samples is reduced.Experiments for the complex matrix effect correction in EDXRF analysis of samples in Pangang showed improved accuracy of the elemental analysis result.
基金the National Natural Science Foundation of China(Grant Nos.62076208,62076207,and U20A20227)the National Key Research and Development Program of China(Grant No.2018YFB1306600)。
文摘Memristive neural network has attracted tremendous attention since the memristor array can perform parallel multiplyaccumulate calculation(MAC)operations and memory-computation operations as compared with digital CMOS hardware systems.However,owing to the variability of the memristor,the implementation of high-precision neural network in memristive computation units is still difficult.Existing learning algorithms for memristive artificial neural network(ANN)is unable to achieve the performance comparable to high-precision by using CMOS-based system.Here,we propose an algorithm based on off-chip learning for memristive ANN in low precision.Training the ANN in the high-precision in digital CPUs and then quantifying the weight of the network to low precision,the quantified weights are mapped to the memristor arrays based on VTEAM model through using the pulse coding weight-mapping rule.In this work,we execute the inference of trained 5-layers convolution neural network on the memristor arrays and achieve an accuracy close to the inference in the case of high precision(64-bit).Compared with other algorithms-based off-chip learning,the algorithm proposed in the present study can easily implement the mapping process and less influence of the device variability.Our result provides an effective approach to implementing the ANN on the memristive hardware platform.
文摘南水入冀新水情下,百泉泉域地下水环境发生改变,岩溶地下水地球化学过程有待查明。综合利用数值模拟、机器学习(自组织聚类)和同位素(δD和δ^(18)O)等方法系统揭示了矿业活动与南水入冀下百泉泉域岩溶地下水地球化学过程,并基于熵变权水质指数(Entropy-weighted water quality index,EWQI)进行了水质分级评价。南水入冀后,百泉泉域岩溶地下水位整体抬升。时间上,呈现出既有年际动态变化又有年内季节变化特征。空间上,补给区表现为剧变型,而径流、排泄区呈缓变型。地下水降落漏斗主要分布在泉域东南部的煤、铁矿密集区。泉域岩溶地下水呈弱碱性,水化学类型以Ca-HCO_(3)型和Ca-SO_(4)型为主导。主要阴阳离子质量浓度遵循ρ(HCO_(3)^(-))>ρ(SO_(4)^(2-))>ρ(Cl^(-))和ρ(Ca^(2+))>ρ(Mg^(2+))>ρ(Na^(+))>ρ(K^(+))的顺序。各离子沿着径流路径呈现出逐渐增大的空间分布特征。岩溶地下水化学成分主要受岩石(方解石、白云石和石膏)风化溶解和反向阳离子交换作用主导。人为活动对泉域岩溶地下水系统中的SO_(4)^(2-)和NO_(3)^(-)质量浓度有一定程度影响。岩溶地下水来源于大气降水,并且在入渗前发生了二次蒸发作用,氘盈余值在径流过程中有所降低。水质评价结果表明,岩溶地下水质量整体优于第四系地下水,分别有50%的岩溶水和37.5%的第四系水样满足饮用目的。TDS、ρ(SO_(4)^(2-))和ρ(NO_(3)^(-))是影响泉域地下水水质的关键指标。引起泉域岩溶地下水系统水质恶化的潜在人类活动主要包括矿山排水、农业灌溉和城市污水排放。通过水质分级评价,提出了泉域地下水环境保护措施。研究结果将有助于为百泉泉域岩溶地下水资源的供水安全和地下水环境保护治理提供参考。
