artificial neural network example matlab

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Ngày tải lên: 28/04/2014, 10:06

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Ngày tải lên: 22/07/2014, 02:20

Ngày tải lên: 07/11/2014, 18:24

... the neural network 2.2 Neural Network In this subsection, text extraction from static image or video sequences is accomplished using the back-propagation (BP) algorithm on a neural network. ... 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 ... 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 is simpler...

Ngày tải lên: 05/11/2012, 14:51

... Binarization result IV. CONCLUSION AND FUTURE WORKS A neural network based method is discussed in this paper. The features used for the neural network are not only the spatial characteristics but ... 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 ... Backpropagation neural network can handle any nonlinear relationship after training including the complicated inter- relationship between the features. Making use of neural networks will also...

Ngày tải lên: 05/11/2012, 14:54

... DESIGN ARTIFICIAL NEURAL NETWORK MODEL Neural networks are computer models that mimic the knowledge acquisition and organization skills of the human brain. Since, the characteristics of a neural ... GW (1992). " ;Neural network modeling of the mechanical behavior of sand," Proc. 9 th Conf. ASCE, New York, pp 421-424. Garson, GD (1991). "Interpreting neural- network connection ... In this study, a back-propagation neural network model for estimating of proper strain rate form soil parameter is proposed. The back-propagation neural network program adopted in the present...

Ngày tải lên: 22/03/2013, 15:01

Ngày tải lên: 05/09/2013, 14:58

Ngày tải lên: 12/09/2013, 16:20

... gọn như sau : Mạng nhiều lớp neuron CHƯƠNG 2 MÔ HÌNH MẠNG NEURAL NETWORKS Mô hình mạng Neural tổng quát có dạng như sau : Ngày nay mạng Neural có thể giải quyết nhiều vấn đề phức tạp đối với con ... định dạng của dữ liệu vào ảnh hưởng đến việc mô phỏng của mạng. Có hai loại mạng static network và dynamic network. Hai kiểu vector đầu vào cơ bản là kiểu xảy ra đồng thời (concurrently) và kiểu ... trong lớp a : vector ngõ ra của lớp neuron Hàm truyền Có rất nhiều hàm truyền áp dụng trong Neural Networks, trong đó ba hàm thường sử dụng nhất là Hard Limit, Linear, Log-Sigmoid. Tổng quát...

Ngày tải lên: 29/09/2013, 06:20

... Stanford AI Lab http://ai.stanford.edu/~nilsson [4] Offline Handwring Recognition Using Artificial Neural Networks â 2000, Andrew T.Wilson University of Minnesota, Morris ... Tính toán lỗi (error), điểm ra (output) và trọng số (weight) thường xuyên. - Xây dựng mạng Neural Network. 1) Huấn luyện mạng Lưu đồ giải thuật huấn luyện mạng của chương trình: 2) Thực ... Minh Ánh. Nghiên cứu và ứng dụng mạng neural trong nhận dạng chữ viết tay tiếng Việt. Khóa luận tốt nghiệp đại học 2005, Đại học Công Nghệ, ĐHQGHN. [3] Artificial Intelligence and cognitive...

Ngày tải lên: 06/10/2013, 20:20

... method for neural networks, in Neural Networks for Speeach and Image Processing, R.J. Mammone, Ed., Chapman & Hall, Boca Raton, FL, 1993. [10] A. Krogh and J. Vedelsby, Neural networks ensembles, ... 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, ... (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...

Ngày tải lên: 12/12/2013, 23:15

... 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 bio- logical neural ... basic neural network structures and how they impact signal processing algorithms and applications. A challenge in surveying the field of neural network paradigms is to identify those neural network structures ... for integrating neural networks with other signal processing algorithms. Another important issue is how to evaluate neural network paradigms, learning algorithms, and neural network structures...

Ngày tải lên: 12/12/2013, 23:15

... 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 ... CRC Press LLC 4 Neural Network Applications for Group Technology and Cellular Manufacturing 4.1 Introduction 4.2 Artificial Neural Networks 4.3 A Taxonomy of Neural Network Application for ... Deterministic neural network models do not have the capability to escape from local optimal solution. Stochastic neural network models attempt to avoid local optimal solutions. Stochastic neural network...

Ngày tải lên: 17/12/2013, 06:15

... 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 recur- rent neural networks are two major classes of artificial neural networks. Feedforward neural networks, Jun Wang The Chinese University of ... The neural network models used were multilayer feedforward networks, MAXNET, Hopfield networks, ART networks, and stochastic networks. The knowledge acquisition capabilities of neural networks made...

Ngày tải lên: 17/12/2013, 06:15

... the neural network topology with the peripheral circuits to generate the PWM waves. It consists of a 1–24–12 network with sigmoidal activation function for middle and output layers. The network ... VOL. 38, NO. 3, MAY/JUNE 2002 Fig. 7. Feedforward neural- network (1–24–12)-based space-vector PWM controller. Fig. 8. Segmentation of neural network output for U -phase P states. and signals ... therefore, the SVM algorithm to be implemented in a neural network is considerably more complex. In the proposed scheme, a three-layer feedforward neural network receives the command voltage and angle...

Ngày tải lên: 22/12/2013, 08:16