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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Barron Type Spaces in Neural Network Approximation
神经网络 巴伦类型空间 经典函数空间
2023/4/13
We shall discuss various Barron type spaces arising from neural networks. The relations among these spaces will be clarified, and we shall also establish the relationship between Barron type spaces an...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Deep neural network approximation to inverse conductivity problems for elliptic equations
椭圆方程 反电导率 深度神经网络
2023/4/14
The focus of this talk is on the numerical methods used to identify parameters in partial differential equations. Typically, an optimization approach is used to solve this class of inverse problems, w...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：A two-stage physics-informed neural network method based on conserved quantities and applications in localized wave solutions
守恒量 两阶段物理信息 神经网络方法 局部波解
2023/5/5
With the advantages of fast calculating speed and high precision, the physics-informed neural network method opens up a new approach for numerically solving nonlinear partial differential equations. B...
Artificial intelligence and machine learning have become crucial tools for medical imaging, autonomous vehicles and many other applications, but engineers warn that the exponential increase in compute...
DEEP CONVOLUTIONAL NEURAL NETWORK FOR AUTOMATIC DETECTION OF DAMAGED PHOTOVOLTAIC CELLS
UAV, monitoring/inspection Anomaly Detection Deep Learning Photovoltaic Panels Thermography Classification
2018/6/4
The number of distributed Photovoltaic (PV) plants that produce electricity has been significantly increased, and issue of monitoring and maintaining a PV plant has become of great importance and invo...
Stanford researchers create a high-performance,low-energy artificial synapse for neural network computing
Stanford researchers high-performance low-energy artificial synapse neural network computing
2017/3/14
For all the improvements in computer technology over the years, we still struggle to recreate the low-energy, elegant processing of the human brain. Now, researchers at Stanford University and Sandia ...
Dopamine Modulation of Two Delayed Rectifier Potassium Currents in a Small Neural Network
Potassium Currents Small Neural Network
2015/8/25
Gruhn, Matthias, John Guckenheimer, Bruce Land, and Ronald
M. Harris-Warrick. Dopamine modulation of two delayed rectifier potassium
currents in a small neural network. J Neurophysiol 94: 2888–2900,...
KNOWLEDGE-BASED NEURAL NETWORK FOR LINE FLOW CONTINGENCY SELECTION AND RANKING
MW security assessment Energy Management Centers Fuzzy rules Domain Knowledge IEEE 14-bus system
2015/7/31
The Line flow Contingency Selection and Ranking (CS & R) is performed to rank the critical contingencies in order of their severity. An Artificial Neural Network based method for MW security assessmen...
Application of Artificial Neural Network Technology in Water Color Remote Sensing Inversion of Inland Water Body Using Tm Data
Artificial Neural Network Model Water Color Remote Sensing Extraction Lake Landsat Image
2015/7/8
For water color remote sensing study of inland water body, terrestrial satellite is often a good data source, because it has high spatial
resolution. However, the precision of water color remote sens...
Enhanced Self-Organizing Map Neural Network for DNA Sequence Classification
Bioinformatics Artificial Neural Networks Self-Organizing Map Classification Sequence Alignment
2013/1/28
The artificial neural networks (ANNs), among different soft computing methodologies are widely used to meet the challenges thrown by the main objectives of data mining classification techniques, due t...
Hybrid Neural Network Architecture for On-Line Learning
Neural Networks Instantaneously Trained Networks Back-Propagation On-Line Learning
2013/1/28
Approaches to machine intelligence based on brain models use neural networks for generalization but they do so as signal processing black boxes. In reality, the brain consists of many modules that ope...
An Intelligent Machine Condition Monitoring System Using Time-Based Analysis: Neuro-Fuzzy Versus Neural Network
Condition Monitoring Time Analysis Neuro-Fuzzy
2010/1/15
Monitoring and predicting machine components' faults play an important role in maintenance actions. Developing an
intelligent system is a good way to overcome the problems of maintenance management. ...
基于改进Harris角点提取的摄像机神经网络标定技术（Neural Network Technique on Camera Calibration Based on Improved Harris Corner Extraction Method）
摄像机标定 神经网络 Harris角点
2009/9/11
以前馈型BP神经网络进行双目立体视觉系统的摄像机标定研究，基于Harris角点提取，提出了增加约束的改进方法，从而提高网络训练样本集的数据精度；探讨了神经网络的欠泛化、过泛化问题，综合运用归一化、提前终止等多种策略，进一步提高网络泛化能力，并与经典标定方法进行对比。试验结果表明，该方法能够获得较高的摄像机标定精度。
Inverse Control of Cable-Driven Parallel Mechanism Using Type-2 Fuzzy Neural Network
Inverse control type-2 fuzzy logic neural network parallel mechanism
2009/9/9
The leveling adjustment process of cable-driven parallel mechanism is challenging due to the difficulty to obtain an accurate mathematical model and the fact that different sources of uncertainties ex...
An Implicit Surface Modeling Technique Based on a Modular Neural Network Architecture
Geometric Modeling Implicit Surfaces Neural Networks
2009/7/28
Independently from artificial intelligence applications, an artificial neural network can be viewed as a powerful tool for function reconstruction. Previous papers used this property to model an impli...