artificial neural network software for excel

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

Ngày tải lên : 17/02/2014, 22:20

... Multilayer feedforward networks are universal approximators. Neural Networks 2, 359–366. Jain, A., Zongker, D., 1997. Feature selection: evaluation, application and small sample performance. IEEE ... the performance function of regularized mean squared error (RMSE), hyperbolic sigmoid tangent for the hidden layers and linear for the output layer. The performance assessment was performed in ... in this study. The MLP was applied for prediction by training the network to output the next day value of NO 2 (T+24 h, where T is the forecasting point) of a forecasted pollutant, given an input...

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a facial expression classification system integrating canny, principal component analysis and artificial neural network

Ngày tải lên : 28/04/2014, 10:06

... 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 ... MLP uses the algorithm of Gradient Back-Propagation for training to update W. B. Structure of MLP Neural Network MLP Neural Network applies for seven basic facial expression analysis signed ... 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...

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facial expression classification based on multi artificial neural network

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 ... at present is to use Artificial Neural Network for the pattern classification. Artificial Neural Network will be trained with the patterns to find the weight collection for the classification ... Artificial Neural Network (MANN), applying for pattern or image classification with parameters (m, L), has m Sub -Neural Network (SNN) and a global frame (GF) consisting L Component Neural Network...

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a comparison of neural network architectures for

Ngày tải lên : 28/04/2014, 10:10

... we describe the development and use of an artificial neural network architecture for recognizing handwritten digit data. The feed-forward neural network, which was implemented in Java, was ... Specifically, for the study described in this paper, we focused on the use of neural network learning techniques for handwritten digit recognition. Our objective was two-fold: to test the neural network ... variety of network parameters and sizes, and to determine the best network structure and settings for the handwritten digit data set. The results provide evidence for the use of neural network...

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backpropagation artificial neural network in c++ - codeproject

Ngày tải lên : 28/04/2014, 10:10

... your test set, for example, varying it between 0.0 and 1.0. Neural Network Classes The neural network is composed from the following classes: ANNetwork ANNLayer ANeuron ANLink The ANNetwork class ... negative classes, and train it for 1000 epochs. The neural network file format is described in my Face Detection article. To start with random initialized weights before the training session, you ... application for backprop training are optional. You may use them for validation and testing of your network, for input data normalization, and error limits during training process. >ann1dn t network. nn...

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designing and implementing a neural network library for handwriting detection, image analysis etc

Ngày tải lên : 28/04/2014, 10:10

... the model. NetworkHelper training data elements. NeuralNetwork A generic neural network. This is a concrete implementation of INeuralNetwork NeuralNetworkCollection A collection of neural networks Neuron ... understand. 5.4. A Neural Network In BrainNet library Now, let us see how the Neural Network is implemented. Any concrete neural network should implement the INeuralNetwork interface. INeuralNetwork interface ... 4-4-2 neural network with 4 neurons in input layer, 4 neurons in hidden layer and 2 neurons in output layer. An artificial neural network can learn from a set of samples. For training a neural network, ...

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a neural network model for limb trajectory formation

Ngày tải lên : 28/04/2014, 10:16

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neural network models for formation and control

Ngày tải lên : 28/04/2014, 10:16

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báo cáo hóa học: " A biologically inspired neural network controller for ballistic arm movements" ppt

Ngày tải lên : 19/06/2014, 10:20

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Báo cáo hóa học: " Research Article Comparing Robustness of Pairwise and Multiclass Neural-Network Systems for Face Recognition" pot

Ngày tải lên : 22/06/2014, 19:20

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A self organizing neural network model for a mechanism of pattern recognition unaffected by shift in position

Ngày tải lên : 08/07/2014, 17:02

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So sánh hai mô hình dự báo tỷ suất sinh lời chứng khoán. Mô hình hồi quy truyền thống và mô hình Artificial Neural Network

Ngày tải lên : 24/11/2014, 01:42

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Báo cáo nghiên cứu khoa học: " NEURAL NETWORK CONTROL OF PNEUMATIC ARTIFICIAL MUSCLE MANIPULATOR FOR KNEE REHABILITATION" pps

Ngày tải lên : 22/07/2014, 02:20

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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

Ngày tải lên : 22/12/2013, 08:16

... processed through a logic block to generate the PWM outputs. - for for for for for for for for for for (5) - for for for for for for for for for for (6) 664 IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. ... expressions in mode 1 can be derived as - for for for for for for (3) - for for for for for for (4) where and denotes the sector name. Similarly, the corresponding expressions for mode 2 can be derived as ... 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 only. Similar operations are performed...

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Tài liệu Fuzzy Neural Network and Wavelet for Tool Condition Monitoring ppt

Ngày tải lên : 23/01/2014, 01:20

... the fuzzy neural network and wavelet transforms to TCM. First, the fuzzy neural network and the wavelet transforms are respectively introduced. Second, the continuous wavelet transforms (CWT) ... Fuzzy Neural Network and Wavelet for Tool Condition Monitoring 15.1 Introduction 15.2 Fuzzy Neural Network 15.3 Wavelet Transforms 15.4 Tool Breakage Monitoring with Wavelet Transforms ... wavelet transforms [2], fuzzy inference [3–5], fuzzy neural networks [6–9], etc., have been established, in which all forms of tool condition can be monitored. Fuzzy systems and neural networks...

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Tài liệu A Backpropagation Neural Network for Computer Network Security doc

Ngày tải lên : 14/02/2014, 16:20

... Cheung and Z. Wang, 2004. A chaotic -neuralnetwork- based encryption algorithm for JPEG2000 encoded images. Advances in Neural Networks, Intl. Symp. Neural Networks Proc., Part II, Lecture Notes ... 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, ... values for N and N'. As an example, if N=5 and N' = 1, then these values generate a space of 1029 times larger than that of DES. Artificial neural networks (ANNs): A neural network...

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Software Design for Six Sigma: A Roadmap for Excellence docx

Ngày tải lên : 17/03/2014, 19:20

... INTRODUCTION TO SOFTWARE DESIGN FOR SIX SIGMA (DFSS) 171 8.1 Introduction / 171 8.2 Why Software Design for Six Sigma? / 173 8.3 What is Software Design For Six Sigma? / 175 8.4 Software DFSS: ... reliability, and quality for a given software product. The Carnegie Mellon Software Engineering Institute (SEI) has carried out the reﬁned work for Personal Software Process (PSP), Team Software Process ... Axiom 2 in Software DFSS / 352 References / 354 Bibliography / 355 14 SOFTWARE DESIGN FOR X 356 14.1 Introduction / 356 14.2 Software Reliability and Design For Reliability / 357 14.3 Software...

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Báo cáo khoa học: "Neural Network Probability Estimation for Broad Coverage Parsing" doc

Ngày tải lên : 24/03/2014, 03:20

... method for automati- cally inducing a finite set of features for represent- ing the derivation history. The method is a form of multi-layered artificial neural network called Simple Synchrony Networks ... to represent the unbounded parse history. We perform this induction using an artificial neural network architecture, called Sim- ple Synchrony Networks (SSNs) (Lane and Hen- derson, 2001; Henderson, ... (becoming [S-VP ]). These transforms are undone before any evaluation is performed on the output trees. We do not believe these transforms have a major impact on performance, but we have not currently...

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Software Design for Six Sigma: A Roadmap for Excellence doc

Ngày tải lên : 30/03/2014, 03:20

... Standard for a Software Quality Metrics Methodology IEEE Std 1228-1994 Standard for Software Safety Plans IEEE Std 1233–1996 Guide for Developing System Requirements Speciﬁcations IEEE Std 16085 Software ... and evaluation of performance. For a software product to have this software quality, the design must not be complex. A sample of questions that can be used to measure the software testability: www.it-ebooks.info ... the current task’s information to the new task’s information. Task- speciﬁc information commonly includes register information and the current program counter. The task information that is saved...

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neural network for beginners (part 1 of 3) - codeproject

Ngày tải lên : 28/04/2014, 10:10

... multi-layer neural networks. As this article is mainly geared towards dealing with single layer networks, let's dicuss those further: Single layer neural networks Single-layer neural networks ... target vectors for input vectors close to the previously unseen input vector P. So what can we use do with neural networks Well if we are going to stick to using a single layer neural network, the ... (perceptron) networks. The next part of this article series will show how to do this using muti-layer neural networks, using the back propogation training method. Well that's about it for this...

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