artificial neural network ppt slideshare

... USING ARTIFICIAL NEURAL NETWORK In this paper, we use Multi Layer Perceptron (MLP) Neural Network with back propagation learning algorithm. A. Multi layer Perceptron (MLP) Neural Network ... with Rapid Facial Expression Classification Using Artificial Neural Network [10], Facial Expression Classification Using Multi Artificial Neural Network [11] in the same JAFFE database. TABLE ... Facial Expression Classification Using Artificial Neural Networks [10] 73.3% Facial Expression Classification Using Multi Artificial Neural Network [11] 83.0% Proposal System...

Ngày tải lên: 28/04/2014, 10:06

... many Neural Networks together, so we call it Multi Artificial Neural Network (MANN). 3 Multi Artificial Neural Network apply for image classification 3.1 The proposal MANN model Multi Artificial ... any in L given classes, the Artificial Neural Network identify and report results to the outside given classes. In this paper, we propose the Multi Artificial Neural Network (MANN) model to apply ... into responsive class using a Neural Network called Sub Neural Network (SNN) of MANN. Lastly, we use MANN’s global frame (GF) consisting some Component Neural Network (CNN) to compose the classified...

Ngày tải lên: 28/04/2014, 10:06

Ngày tải lên: 28/04/2014, 10:10

Ngày tải lên: 20/06/2014, 22:20

Ngày tải lên: 24/11/2014, 01:42

... 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

... 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. ... 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 ... à [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 ì 5), learning...

Ngày tải lên: 23/01/2014, 01:20

Ngày tải lên: 19/06/2014, 10:20

Ngày tải lên: 20/06/2014, 00:20

Ngày tải lên: 21/06/2014, 20:20

Ngày tải lên: 22/06/2014, 11:20

Ngày tải lên: 22/07/2014, 02:20

... 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