stuttgart neural network simulator
Automatic text extraction using DWT and Neural Network
... algorithm on a neural network The training of the neural network is based on the features we obtain from the DWT detail component sub-bands As shown in Figure 6, the proposed neural network architecture ... regions Those features are used as the input of a neural network for training based on the back-propagation algorithm for neural networks After the neural network is well trained, new input data will ... next subsection, a neural network is employed to learn the features of candidate text regions obtained from those detail component sub-bands Finally, the well trained neural network is ready to...
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Text extraction from name cards using neural network
... i.e., width and height, there are totally 14 features used for the neural network analysis D Contours classification using neural network We extract the above features which are helpful for classification ... a Backpropagation neural network can handle any nonlinear relationship after training including the complicated interrelationship between the features Making use of neural networks will also ... not set different thresholds for different type of images To train the neural network, we create a Backpropagation neural network consisting of 14 inputs nodes, 20 hidden nodes, and output node...
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Hybrid energy system evaluation in water supply system energy production: neural network approach
... supply systems with complementary renewable energy sources [3] 2.4 Artificial neural networks Artificial neural networks (ANN) have been used in water distribution systems to model the degradation ... testing The conception of a new neural network hybrid energy model which can be compared with an energy configuration model and economical simulator – CES (e.g HOMER simulator) for limited conditions ... may be used in training process and in a reliable neural network tests together with an hydraulic and power simulator model – HPS (e.g EPANET simulator) , alternating flow rates, diameters and...
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MÔ HÌNH NEURAL NETWORK TRONG DỰ BÁO TÀI CHÍNH
... điều khiển, Neural Network ứng dụng Sự thành công nhanh chóng mạng Neural Network số nhân tố sau: Năng lực : Neural Network kỹ thuật mô tinh vi, có khả mô hàm phức tạp Đặc biệt, Neural Network ... luận Tài liệu tham khảo Phụ lục CHƯƠNG 1: MÔ HÌNH NEURAL NETWORK TRONG DỰ BÁO TÀI CHÍNH 1.1 GIỚI THIỆU SƠ LƯỢC VỀ MÔ HÌNH NEURAL NETWORK Neural Network vài năm trở lại nhiều người quan tâm áp dụng ... dụng biết cách áp dụng thành công Neural Network thấp nhiều người sử dụng phương pháp thống kê truyền thống… 1.2 NỀN TẢNG CỦA MÔ HÌNH NEURAL NETWORK Neural Network phát triển từ nghiên cứu trí...
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Mô hình mạng neural network
... Hàm truyền Có nhiều hàm truyền áp dụng Neural Networks, ba hàm thường sử dụng Hard Limit, Linear, Log-Sigmoid Tổng quát với hàm truyền có ... DỮ LIỆU Cấu trúc đònh dạng liệu vào ảnh hưởng đến việc mô mạng Có hai loại mạng static network dynamic network Hai kiểu vector đầu vào kiểu xảy đồng thời (concurrently) kiểu xảy liên tục theo...
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043_Nghiên cứu mạng Neural Network trong nhận dạng chữ viết
... lớp, lớp đầu vào (input), lớp ẩn lớp đầu (ouput) Chức chương trình: - Xây dựng mạng Neural Networks khởi tạo trọng số (Weight) cách thường xuyên - Phân tích ảnh điểm ảnh cho kí tự nhận ... xuyên - Tính toán lỗi (error), điểm (output) trọng số (weight) thường xuyên - Xây dựng mạng Neural Network 3) Kết - Số lượng kí tự=90 - Tốc độ học (Learning rate)=150 - Sigmoid slope=0.014 Bảng ... Stanford AI Lab http://ai.stanford.edu/~nilsson [4] Offline Handwring Recognition Using Artificial Neural Networks 2) Thực nghiệm Lưu đồ giải thuật huấn luyện mạng chương trình: © 2000, Andrew T.Wilson...
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Tài liệu Handbook of Neural Network Signal Processing P2 docx
... (LVQ) neural network The above discussion is summarized in Table 1.5 TABLE 1.5 Pattern Classification Methods and Corresponding Neural Network Implementations Pattern Classification Methods Neural Network ... generalized state vector s as an input to a neural network and obtain the output y(t) from the output of the neural network One such example is the time-delayed neural network (TDNN) that can be described ... three complementary parts: neural network fundamentals, neural network solutions to statistical signal processing problems, and signal processing applications using neural networks In the first part,...
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Tài liệu Handbook of Neural Network Signal Processing P1 ppt
... Artificial Neural Network (ANN) Models — An Overview 1.2.1 Basic Neural Network Components A neural network is a general mathematical computing paradigm that models the operations of biological neural ... systems, applications of neural networks to biomedical image processing, and a hierarchical fuzzy neural network for pattern classification The theory and design of artificial neural networks have advanced ... nature of neural networks, the ability of neural networks to learn from their environments in supervised and/or unsupervised ways, as well as the universal approximation property of neural networks...
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Tài liệu Neural Network Applications ppt
... 4.4 Introduction Artificial Neural Networks A Taxonomy of Neural Network Application for GT/CM Conclusions 4.1 Introduction Recognizing the potential of artificial neural networks (ANNs) for pattern ... computational performance and application domain for various neural network architectures 4.2 Artificial Neural Networks Artificial neural networks have emerged in recent years as a major means for ... Deterministic neural network models not have the capability to escape from local optimal solution Stochastic neural network models attempt to avoid local optimal solutions Stochastic neural network...
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Tài liệu Neural Network Applications in Intelligent doc
... types of neural networks included ART networks, Hopfield networks, and SOM neural networks Weaknesses of neural networks for modeling and design of manufacturing systems result from neural networks ... parallel distributed fashion Feedforward neural networks and recurrent neural networks are two major classes of artificial neural networks Feedforward neural networks, ©2001 CRC Press LLC such as ... with other stochastic neural networks The presented neural network overcame the local minimum problem existing in deterministic neural networks The proposed neural network was comparable to conventional...
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Tài liệu A neural-network-based space-vector PWM controller for a three-level voltage-fed inverter induction motor drive doc
... values can be a neural network Then, solved from the equations corresponding to the superimposed Figs and MONDAL et al.: A NEURAL- NETWORK- BASED SPACE VECTOR PWM CONTROLLER III NEURAL- NETWORK- BASED ... et al.: A NEURAL- NETWORK- BASED SPACE VECTOR PWM CONTROLLER Fig Explanation of timer and logic operation Fig 10 Machine line voltage and phase current waves in mode (10 Hz) (a) Neural- network- based ... multiplication with the voltage Fig shows the neural network topology with the signal peripheral circuits to generate the PWM waves It consists of a 1–24–12 network with sigmoidal activation function...
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Tài liệu Network Simulator ns-2 pptx
... Introduction Interface Simulator Tcl and OTcl TclCL Wired network Wireless network Program Assignment Introduction NS-2: network simulator version Discrete event simulator Packet level ... traffic generation 36 Network Simulator ns-2 Part III: Wireless Network Wireless Network Wireless network Nodes can move No explicit “links” used to connect nodes Wireless network extension ... Elements Create the event scheduler (simulator) [Setup tracing] Create network topology [Setup routing] [Insert error modules /network dynamics] Create connection (transport) Create...
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Tài liệu Neural Network Applications to Manufacturing Processes: Monitoring and Control pptx
... estimation using a neural network model FIGURE 12.9 The neural network architecture (a) A laser surface hardening process (b) The layer geometry estimation using a neural network model generate ... Various neural network based monitoring and control schemes (a) A neural identifier combined with an adaptive controller (b) A gain-tuning neural network controller (c) A feedforward neural controller ... neural network (ANN) approaches have been applied to solder joint inspection due to learning capability and nonlinear classification performance Among many neural network approaches, the LVQ neural...
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TIỂU LUẬN môn học CHUYÊN đề đề tài NEURAL MODEL ANH NETWORK ARCHITECTURES (NẺURAL NETWORK DESIGN)
... độ không khí, vận tốc gió độ ẩm, có đầu vào cho mạng Để nghiên cứu nơron hai đầu vào, sử dụng Neural Network Design Demonstration Two-Input Neuron (nnd2n2) Các cấu trúc mạng Thông thường nơron,...
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Tài liệu Fuzzy Neural Network and Wavelet for Tool Condition Monitoring ppt
... neural network is presented to describe the relationship between the tool wear conditions and the monitoring features 15.2 Fuzzy Neural Network 15.2.1 Combination of Fuzzy System and Neural Network ... the neural network The model in Figure 15.2(b) shows that the fuzzy system can be controlled by the neural network; the inference processing of the fuzzy system is responded to by the neural network ... learning rates , µ∈[0,1] To test the fuzzy neural network (FNN), it is compared with the BP neural networks (BPNN) [22] Under the same conditions (training sample, networks structure (5 × 5), learning...
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Tài liệu A Backpropagation Neural Network for Computer Network Security doc
... neurons in the output layer Figure shows the architecture of the neural network To implement our neural network we used the Neural Network Toolbox in MATLAB At the beginning of the learning process, ... symmetric cryptography based on chaotic signal generator and a clipped neural network Advances in Neural Networks-ISNN, Intl Symp Neural Networks Proc., Part II Lecture Notes in Computer Science, 3174: ... Chen, A Cheung and Z Wang, 2004 A chaotic -neural- network- based encryption algorithm for JPEG2000 encoded images Advances in Neural Networks, Intl Symp Neural Networks Proc., Part II, Lecture Notes...
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Tài liệu Evolving the neural network model for forecasting air pollution time series pdf
... Geophysical Research 90 (C5), 8995–9005 Yao, X., 1999 Evolving artificial neural networks Proceedings of the IEEE Transactions on Neural Networks 87 (9), 1423–1447 ... Arbor Hornik, K., Stinchcombe, M., White, H., 1989 Multilayer feedforward networks are universal approximators Neural Networks 2, 359–366 Jain, A., Zongker, D., 1997 Feature selection: evaluation, ... (Hornik et al., 1989), which states that a twohidden layer network may achieve the same accuracy with a single hidden layer neural network with fewer hidden layer neurons However, the use of...
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Tài liệu Thesis "Neural Network Control" doc
... addresses two neural network based control systems The first is a neural network based predictive controller System identification and controller design are discussed The second is a direct neural network ... 4.3 89 90 92 Neural Network Model Based Predictive Controller Direct Neural Network Controller Future Work A Matlab Source Code A.1 Neural Network Model ... Training The process of tuning the neural network weights in order to achieve a certain kind of performance of the neural network is called training 1.2 The Neural Network In general, some kind of...
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