associative memory in artificial neural network

... for predicting proper strain rate involved three phases First, data collection phase involved gathering the data for use in training and testing the neural network. A large training data reduces ... of under-sampling the nonlinear function, but increases the training time. To improve training, preprocessing of the data to values between 0 and 1 was carried out before presenting the patterns ... squared error over all the training patterns was minimized. Experiment were carried out using a number of combinations of input parameters to determine the neural network model that gave the...

Ngày tải lên: 22/03/2013, 15:01

... should be divided into several sets (training, testing, production, on-line, remaining). The training set is used to adjust the interconnection weights of the MPNN model. The testing set is used ... local minimum far from the global one. During the learning process, the network should be periodically tested on the testing set (not included in the training set) www.intechopen.com Artificial ... perceptron neural network (Božnar et al, 1993), but in the following years we use an artificial neural networks in several other applications that differ very much each another. In this article we intend...

Ngày tải lên: 29/03/2014, 21:20

... The binary floating point file format is expedient when you have a large amount of data. The data is saved in a separate file as a sequence of floating point numbers in binary format, using 4 ... 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 data1_file ... layer: ANNetwork::ANNetwork(const wchar_t *fname); ANNetwork::ANNetwork(int layers_number, int *neurons_per_layer); int nerons_per_layer[4] = {128, 64, 32, 10}; ANNetwork *ann = new ANNetwork(4,...

Ngày tải lên: 28/04/2014, 10:10

... every other neuron in a Hopfield Neural Network. A Hopfield Neural Network can be trained to recognize certain patterns. Training a Hopfield Neural Network involves performing some basic matrix ... particularly sure what final outcome is being sought. Neural networks are often employed in data mining do to the ability for neural networks to be trained. Neural networks can also be used ... propagation refers to the way in which the neurons are trained in this sort of neural network. Chapter 3 begins your introduction into this sort of network. A Fixed Wing Neural Network Some researchers...

Ngày tải lên: 14/02/2014, 20:20

... of Neural Networks 163 Hazem M. El-Bakry Chapter 9 Applying Artificial Neural Network Hadron - Hadron Collisions at LHC 183 Amr Radi and Samy K. Hindawi Chapter 10 Applications of Artificial Neural ... training examples needed, convergence to an attractor in a single step and geometric increase (rather than linear) in the number of classes with the number of nodes. The disadvantage is the increasing ... [12, 13]. The prevailing concepts in neurodynamics are based on neural networks, which are Newtonian models, since they treated neural microscopic pulses as point processes in trigger zones and...

Ngày tải lên: 15/03/2014, 23:20

... training was completed, the validation test followed using the remaining data that were not used for training. Results of training and validation test are shown in Figure 11. Since data points ... Bridge since appropriate strain readings could be acquired for obtaining information about number of axles, speed and axle spacings of a vehicle. Also, appropriate strain readings for calculating ... Calculating an Influence Line from Direct Measurements. Proceedings of the ICE - Bridge Engineering, 2006, 159, 31-34. 7. McNulty, P.; O’Brien, E.J. Testing of Bridge Weigh -In- Motion System in a...

Ngày tải lên: 28/04/2014, 10:02

... Rapid Facial Expression Classification Using Artificial Neural Network [10], Facial Expression Classification Using Multi Artificial Neural Network [11] in the same JAFFE database. TABLE IV. ... Facial Expression Classification Using Artificial Neural Networks [10] 73.3% Facial Expression Classification Using Multi Artificial Neural Network [11] 83.0% Proposal System ... than Rapid Facial Expression Classification Using Artificial Neural Networks [10] and Facial Expression Classification Using Multi Artificial Neural Network [11] (only used ANN). Beside, this...

Ngày tải lên: 28/04/2014, 10:06

... classes. Domains can be joined to form super-domains, of which the original domains are the subdomains. Sup e r-domains inherit the services and attributes of their subdomains. Multiple-inheritance is ... animal learning. MMC offers a framework for constructing, combining, sharing, transforming and verifying ontolo- gies. We conclude that the MMC can serve as an effec- tive tool for neural modeling. But ... discriminant class points position mesh of cells cluster of points neurons firing event time mesh neural clique Our classification example involves a set of 167 points defined by their coordinates in...

Ngày tải lên: 28/04/2014, 10:06

... cues used in our training studies [9, pp. 437-442] are included as outputs of the network. Furthermore, since the activation values of the networks’ output nodes are constrained to lie in the range ... speech parameters. Neural networks have been shown to be efficient and robust learning machines which solve an input-output mapping and have been used in the past to perform similar mappings from acoustics ... 40 seconds were used as train- ing data for the networks. The remaining 10 sec- onds were used as a test set for the trained net- works. The restricted amount of training data avaliable from each...

Ngày tải lên: 28/04/2014, 10:06

... called local training. Phase (2) is to train CNN(s) in GF one-by- one called global training. In local training phase, we will train the SNN 1 first. After that we will train SNN 2 , SNN m . ... local training In the global training phase, we will train the CNN 1 first. After that we will train CNN 2 ,…,CNN L . Fig 8. CNN1 global training On the other approach is building the ... it Multi Artificial Neural Network (MANN). 3 Multi Artificial Neural Network apply for image classification 3.1 The proposal MANN model Multi Artificial Neural Network (MANN), applying for...

Ngày tải lên: 28/04/2014, 10:06

... longer, inducing fatigue, in a following session. A set of trajectory errors will be used as training input of the NF neural network and the corresponding desired output will be built using the ... established that adding noise to the training data in artificial neural learning improves the quality of learning, as measured by the trained networks ability to maximize exploration of the input/output ... con- trol of dynamical systems using neural networks. IEEE Trans Neural Networks 1990, 1:4-27. 23. Matsuoka K: Noise injection into inputs in back-propagation learning. IEEE Transactions on Systems,...

Ngày tải lên: 19/06/2014, 10:20

Ngày tải lên: 19/06/2014, 10:20

... by including these parameters as input during the training phase. In few cases, the network has predicted contradictory trends which are found difficult to be explained. Also, the neural network ... pilling, finger marks, and others. free online editions of InTech Books and Journals can be found at www.intechopen.com Artificial Neural Networks - Industrial and Control Engineering Applications Edited ... 2011 Printed in India A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechweb.org Artificial Neural Networks - Industrial...

Ngày tải lên: 20/06/2014, 00:20

... as the input units of the neural network. They used a back propagation neural network by eight defect samples for off line training. The initial learning rate was 0.1; keeping reducing to 0.01 ... images, segmenting pills appearing on converted gray images, extracting of a pill's feature index, and finally assessing pilling grade by Kohonen self Artificial Neural Networks - Industrial ... 1000 spindle hours; by means of inputs including the processing parameters such as fiber properties, spinning method, and process variables influencing on the yarn properties and spinning performance....

Ngày tải lên: 20/06/2014, 00:20

... complete network by linear connection with linear or nonlinear transformations. The weights were determined by training the neural nets. Once the ANN was trained, it was used for predicting new ... use of neural network is very effective for predicting problems in clothing manufacturing. Xu et al., 1999 used three clustering analysis technique viz. sum of squares, fuzzy and neural network ... prepared using series of textile machinery normally used in needle- punching process for preparation of the fabric samples. Textile materials are compressive in Artificial Neural Networks - Industrial...

Ngày tải lên: 20/06/2014, 00:20

Ngày tải lên: 20/06/2014, 00:20

Ngày tải lên: 20/06/2014, 00:20

Ngày tải lên: 20/06/2014, 00:20

Ngày tải lên: 20/06/2014, 00:20

Ngày tải lên: 20/06/2014, 00:20