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context dependent recurrent neural network language model

Tài liệu Evolving the neural network model for forecasting air pollution time series pdf

Tài liệu Evolving the neural network model for forecasting air pollution time series pdf

Điện - Điện tử

... and comparison of models. Journal of GeophysicalResearch 90 (C5), 8995–9005.Yao, X., 1999. Evolving artificial neural networks. Proceedings of theIEEE Transactions on Neural Networks 87 (9), ... concentration). Neural networks, in particular the multi-layer perceptron(Hornik et al., 1989), provide a flexible and non-lineartool for tackling regression problems in the air qualitymodelling ... (Hornik et al., 1989), which states that a two-hidden layer network may achieve the same accuracywith a single hidden layer neural network with fewerhidden layer neurons. However, the use of...
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Tài liệu Báo cáo khoa học:

Tài liệu Báo cáo khoa học: "Context-dependent SMT Model using Bilingual Verb-Noun Collocation" doc

Báo cáo khoa học

... statistical machinetranslation model as an alternative to the classicalIBM-style model. This model is tightly coupledwith target language model and utilizes bilingual context information. It is ... translationmodels have adopted the noisy-channel based IBMstyle models (Brown et al., 1993):(1)In these model, we have two types of knowledge:translation model, and language model, . The ... word translation model and a bi-gram language model. The bi-gram language model was generated by using CMU LM toolkit(Clarkson et al., 1997). Instead of using a fer-tility model, we allowed...
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Báo cáo khoa học:

Báo cáo khoa học: "Automatic Acquisition of Language Model based on Head-Dependent Relation between Words" pdf

Báo cáo khoa học

... Preliminary experiments We have experimented with three language models, tri-gram model (TRI), bi-gram model (BI), and the proposed model (DEP) on a raw corpus extracted from KAIST corpus ... DEP model with very slight increase in entropy. 5 Conclusions In this paper, we presented a language model based on a kind of simple dependency gram- mar. The grammar consists of head -dependent ... the proposed language model per- forms better than n-gram models in test cor- pus entropy. This means that the reestimation algorithm can find out the hidden information of head -dependent relation...
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Automatic text extraction using DWT and Neural Network

Automatic text extraction using DWT and Neural Network

Kỹ thuật lập trình

... 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...
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Text extraction from name cards using neural network

Text extraction from name cards using neural network

Kỹ thuật lập trình

... 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...
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Mô hình mạng neural network

Mô hình mạng neural network

Quản trị mạng

... gọn như sau :Mạng nhiều lớp neuronCHƯƠNG 2MÔ HÌNH MẠNG NEURAL NETWORKSMô 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 mạngstatic network và dynamic network. Hai kiểu vector đầu vào cơ bản là kiểu xảy ra đồng thời(concurrently) và kiểu ... trong lớpa : vector ngõ ra của lớp neuronHàm truyềnCó rất nhiều hàm truyền áp dụng trong Neural Networks, trong đó ba hàm thường sử dụng nhấtlà Hard Limit, Linear, Log-Sigmoid.Tổng quát...
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043_Nghiên cứu mạng Neural Network trong nhận dạng chữ viết

043_Nghiên cứu mạng Neural Network trong nhận dạng chữ viết

Điện - Điện tử - Viễn thông

... một lớp ẩn và một lớp đầu ra (ouput). Chức năng chính của chương trình: - Xây dựng mạng Neural Networks và khởi tạo trọng số (Weight) một cách thường xuyên. - Phân tích ảnh điểm của những ... 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 ... AI Lab http://ai.stanford.edu/~nilsson [4] Offline Handwring Recognition Using Artificial Neural Networks © 2000, Andrew T.Wilson University of Minnesota, Morris ...
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Tài liệu Handbook of Neural Network Signal Processing P2 docx

Tài liệu Handbook of Neural Network Signal Processing P2 docx

Quản trị mạng

... method for neural networks,in Neural Networks for Speeach and Image Processing,R.J. Mammone, Ed., Chapman & Hall, BocaRaton, FL, 1993.[10] A. Krogh and J. Vedelsby, Neural networks ensembles, ... Chapter 13: Hierarchical Fuzzy Neural Networks for Pattern Classification. In thischapter, Taur, Kung, and Lin introduce the decision-based neural network, a modular network, and its applications ... (LVQ) neural network. The above discussion is summarized in Table 1.5.TABLE 1.5 Pattern Classification Methods and Corresponding Neural Network ImplementationsPattern Classification Methods Neural...
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Tài liệu Handbook of Neural Network Signal Processing P1 ppt

Tài liệu Handbook of Neural Network Signal Processing P1 ppt

Quản trị mạng

... Artificial Neural Network (ANN) Models — An Overview1.2.1 Basic Neural Network ComponentsA neural network is a general mathematical computing paradigm that models the operations of bio-logical neural ... a neural network with cyclic topology contains at least one cycle formed by directedarcs. Such a neural network is also known as a recurrent network. Due to the feedback loop,a recurrent network ... the basic concept of these neural network modelsto prepare the readers for later chapters.1.2.1.1 McCullochand Pitts’ Neuron Model Among numerous neural network models that have been proposed...
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Tài liệu Neural Network Applications ppt

Tài liệu Neural Network Applications ppt

Cơ khí - Chế tạo máy

... Deterministic neural network models do not have the capabilityto escape from local optimal solution. Stochastic neural network models attempt to avoid local optimalsolutions. Stochastic neural network models ... CRC Press LLC 4 Neural Network Applications forGroup Technologyand Cellular Manufacturing 4.1 Introduction 4.2 Artificial Neural Networks 4.3 A Taxonomy of Neural Network Applicationfor ... Sequence -dependent clustering of parts and machines: AFuzzy ART neural network approach, Int. J. Prod. Res., 37(12): 2793-2816.Venugopal, V., 1998, Artificial neural networks and fuzzy models:...
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Tài liệu Neural Network Applications in Intelligent doc

Tài liệu Neural Network Applications in Intelligent doc

Cơ khí - Chế tạo máy

... 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 ... computationalmodels processing information in a parallel distributed fashion. Feedforward neural networks and recur-rent neural networks are two major classes of artificial neural networks. Feedforward neural ... feedforward neural networks. Recurrent neural networks, such as the Hopfield networks, are usually used as computational models forsolving computationally intensive problems. Typical examples of recurrent...
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