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

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

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

... Mechanism of Pattern Recognition Unaffected by Shift in Position Kunihiko Fukushima NHK Broadcasting Science Research Laboratories, Kinuta, Setagaya, Tokyo, Japan Abstract. A neural network model ... to a A-shaped feature situated in a certain area in the input layer, and its response is less affected by the shift in position of the stimulus pattern than that of presynaptic S-cells. Since ... the human brain, the process of recognizing familiar patterns such as al- phabets of our native language differs from that of recognizing unfamiliar patterns such as foreign al- phabets which...
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a  neural  network  model  for  limb  trajectory  formation

a neural network model for limb trajectory formation

... paper we presented a model for the formation of limb trajectories, based on a neural network architec- ture. The task under consideration was that of reaching a target defined in terms of a ... not be learned by a linear network; (iv) after learning, the internal connections became organized into inhibitory and excitatory zones and encoded the main features of the training set; ... of motor redundancy. 1 Introduction This paper deals with the problem of representing and generating unconstrained aiming movements of a limb by means of a neural network architecture. Aiming...
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báo cáo hóa học:

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

... ending points coordinates, become the newdata for the training of the network (phase 3). In this way, a mapping between muscular activations and points of the working space can be attained.The ... in the use of Artificial Neural Networks (ANN) because of their capabilities toadapt and to generalise to new situations. In order to linkthe neural learning/adaptation processes to their artificialreplica, ... The angles q1' and q2' univocally define the spatial configuration of the arm in the arrival point (Cartesian position x a , y a ) (2), that in the early phases of the learning...
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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

... forecastingpoint) of a forecasted pollutant, given an input vectorcontaining earlier air quality measurements at T+0 hand weather observations at T+24 h (simulating a weather forecast). In the training ... imputation of missing values in air quality data sets. Atmospheric Environment, accepted for publication.Karppinen, A. , Joffre, S., Vaajama, P., 1997. Boundary layerparametrization for Finnish regulatory ... particu-larly reducing the need of computational efforts by eliminating irrelevant inputs. In the case of air qualityforecasting this can also imply smaller costs due to thesmaller amount of measurements...
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Báo cáo khoa học:

Báo cáo khoa học: "Self-Organizing Ò-gram Model for Automatic Word Spacing" ppt

... specific information in determining word spacing. In a word, the pro-posed model organizes the windows sizeonline,and achieves high accuracy by removing both datasparseness and information lack.The ... best, a self- organizing -gram model explained below startsfrom bigram.4 Self- Organizing -gram Model To tackle the problem of fixed window size in -gram models, we propose a self- organizing struc-ture ... Program for Machine Learn-ing. Morgan Kaufmann Publishers.D. Ron, Y. Singer, and N. Tishby. 1996. The Power of Amnesia: Learning Probabilistic Automata withVariable Memory Length. Machine Learning,...
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a comparison of neural network architectures for

a comparison of neural network architectures for

... development of new neural network models and theories. Today numerous neural network models and algorithms are available including back propagation learning, competitive learning, Kohonen learning, ... correlation between a feature’s template and the input image. A value of 0 indicates that a feature template did not match the digit image; a value of 1 indicates a complete match; and values in ... for the use of neural network learning techniques for this type of application and data set, and insight about the appropriate design, use, and parameterization of the network to achieve acceptable...
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designing and implementing a neural network library for handwriting detection, image analysis etc

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

... section explains how the training takes place, in a back ward propagation neural network. In a backwardpropagation neural network, there are several layers, and each neuron in each layer is connected ... two interesting functions, TrainNetwork and RunNetwork, for training and running the network. The inputto the TrainNetwork function is an object of TrainingData class. The TrainingData class has ... concepts of BrainNet library.3. Understanding Neural NetworksOne fascinating thing about artificial neural networks is that, they are mainly inspired by the human brain. This doesn'tmean that...
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báo cáo hóa học:

báo cáo hóa học:" Force-feedback interaction with a neural oscillator model: for shared human-robot control of a virtual percussion instrument" doc

... are linked together using a neural oscillator. For instance, see theparadigm suggested in Figure 11. The system mimics a human playing a musical shaker using periodic patterns according to a ... oscillator model developed by Edward Large for sim-ulating rhythm perception. Using a mechanical analog parameterization, wederive a force–feedback model structure that enables a human to share ... for coordinating with a human.2.4.2 Intended coordination Of course interpersonal coordinations canalso be intended. Many researchers seek to fit dynamical models to humancoordination of simple...
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A DISTRIBUTED WATER QUALITY TANK MODEL FOR NITROGEN LOAD REDUCTION BY ARTIFICIAL WETLANDS

A DISTRIBUTED WATER QUALITY TANK MODEL FOR NITROGEN LOAD REDUCTION BY ARTIFICIAL WETLANDS

... and Hayakawa N. (1989). A rainfall-runoff model using distributed data of radar rain and altitude. Proceedings of JSCE, 411/II-12, 135-140. (in Japanese) Nakasone H., Kuroda H., and Kubota K. ... determined by means of a field investigation by using a land-use map and a 1:5,000 map (Fig. 3). The Geographical Survey Institute in Japan publishes elevation data and the land-use map. A channel ... comprising a set of two tanks, is applied to each cell (Fig. 4), and a tank is also applied to a drainage cell. Water and the nitrogen load arrive at the drainage cell and then flow into a drainage...
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