exercising a neural network model

... coordinatetransformation problem and proposed an iterative control learning algorithm Our research dealt with a sensory-motor transformation based on a nonhierarchical layered architecture which translated ... wish to thank Michael Jordan for his constant support and valuable suggestions, and for making available the basic software which implements sequential networks Thanks also go to (in alphabetic ... problems In: Jeannerod M (ed) Attention and performance XIII Erlbaum, Hillsdale, NJ Kawato M, Furukawa M, Suzuki R (1987) A hierarchical neuralnetwork model for control and learning of voluntary movements...

Ngày tải lên: 28/04/2014, 10:16

... matches with that of the standard pattern situated at a certain location, and that, at the same time, the lower part of this input pattern matches with that of the same standard pattern situated ... input layer Figure is a schematic diagram illustrating the interconnections between layers Each tetragon drawn with heavy lines represents an S-plane or a C-plane, and each vertical tetragon drawn ... two-dimensional array of S-cells which extract A- shaped features Since the stimulus pattern "A" contains A- shaped feature at the top, an S-cell near the top of this S-plane yields a large output as shown...

Ngày tải lên: 08/07/2014, 17:02

... observed/measured data Neural network models require a large number of measurements Please cite this article in press as: Mikulandric´ R et al Artificial neural network modelling approach for a biomass ... prediction performance analysis, neural network model changes and model verification Neural network model For utilizing a neural network model (NNM), the prediction model has to learn/to be trained from ... have been analysed Neural network models show good correlation with measured data and good capability to predict biomass gasification process parameters with reasonable accuracy and speed Acknowledgements...

Ngày tải lên: 01/08/2016, 09:32

... operations are signals of all the phases and all the The drive performance was evaluated in detail by simulation with the neural network which was trained and tested offline in 10–1603 V and ... interpolation capability, MONDAL et al.: A NEURAL- NETWORK- BASED SPACE VECTOR PWM CONTROLLER Fig Explanation of timer and logic operation Fig 10 Machine line voltage and phase current waves in ... training and values can be a neural network Then, solved from the equations corresponding to the superimposed Figs and MONDAL et al.: A NEURAL- NETWORK- BASED SPACE VECTOR PWM CONTROLLER III NEURAL- NETWORK- BASED...

Ngày tải lên: 22/12/2013, 08:16

... minimise fluctuation) The data from the years 1996– 1998 was used as training data and data from the year 1999 as model validation data This approach was computationally expensive due to long training ... universal approximators Neural Networks 2, 359–366 Jain, A. , Zongker, D., 1997 Feature selection: evaluation, application and small sample performance IEEE Transactions on Pattern Analysis and Machine ... meteorological data, based on a combination of the data from synoptic stations at Helsinki–Vantaa airport (about 15 km north of Helsinki downtown) and Helsinki–Isosaari (an island about 20 km...

Ngày tải lên: 17/02/2014, 22:20

... alternations apply automatically in Contemporary Standard Russian Analogical forces should thus heavily favor a single form, for example, pobežu Traditional explanations for the gaps, such as homophony ... morphological cause We model the persistence and spread of the Russian verbal gaps with a multi-agent model with Bayesian learning Our model has two kinds of agents, adults and children A model cycle ... homophony avoidance (Švedova 1982) are also unsatisfactory since they can, at best, explain only a small percentage of the gaps Thus, the data suggest that gaps persist in Russian primarily because...

Ngày tải lên: 17/03/2014, 04:20

... estimate on a small dataset, because he did not have a computationally efficient way to train this model, he was not able to test it on the standard datasets The other models he investigates conflate ... model for part-of-speech tagging In Proc Conf on Empirical Methods in Natural Language Processing, pages 133–142, Univ of Pennsylvania, PA Adwait Ratnaparkhi 1999 Learning to parse natural language ... regression and naive bayes In T G Dietterich, S Becker, and Z Ghahramani, editors, Advances in Neural Information Processing Systems 14, Cambridge, MA MIT Press Adwait Ratnaparkhi 1996 A maximum...

Ngày tải lên: 23/03/2014, 19:20

... INeuronStrategy, called BackPropNeuronStrategy (for a backward propagation neural network) A Neural Network is initialized and connections betweens layers are made by a neural network factory A Factory ... trained the network 4.1 Training Phase This section explains how the training takes place, in a back ward propagation neural network In a backward propagation neural network, there are several ... library Understanding Neural Networks One fascinating thing about artificial neural networks is that, they are mainly inspired by the human brain This doesn't mean that Artificial Neural Networks...

Ngày tải lên: 28/04/2014, 10:10

Ngày tải lên: 28/04/2014, 10:16

... trajectory control of an industrial robotic manipulator (Kawasaki-Unimate PUMA260) with prepared nonlinear transformations which were de- rived from a dynamics equation of a manipulator idealized ... in learning control of the robotic manipulator by an inverse-dynamics model made of a three-layer neural network (Fig 5) $\frac {A^ {u}}{*,4}$ In this network, nonlinear transformation was made ... the effect of leaming for faster and quite different movement pattem from the training pattem was marked, that is the network has great capability of learning generalization Regarding the second...

Ngày tải lên: 28/04/2014, 10:16

Ngày tải lên: 28/04/2014, 10:17

Ngày tải lên: 28/04/2014, 10:17

... employ a computable mechanical analog model of a neural oscillator for implementing force–feedback interaction A linear-only version of the mechanical analog model was proposed earlier by Claude Cadoz ... Using a mechanical analog parameterization, we derive a force–feedback model structure that enables a human to share con- trol of a virtual percussion instrument with a “robotic” neural oscillator ... Force–feedback interaction with a neural oscillator model: for shared human–robot control of a virtual percussion instrument Edgar Berdahl∗ (edgar.berdahl@imag.fr), Claude Cadoz (claude.cadoz@imag.fr) and...

Ngày tải lên: 21/06/2014, 17:20

... onset All the features can be updated as long as the information of a new seizure is available Thus the system can adaptively update all related parameters automatically based on available seizure ... occurrence Model (12) is a nonlinear model with Gaussian state space A local linearization technique is applied to nonlinear equations and an approximate linear equation is obtained in (16) A series ... temporal areas The amplitude of data is relative to the real one after sampling them, but all the features will be kept the same For each patient, there are datasets called “ictal,” and “interictal,”...

Ngày tải lên: 21/06/2014, 20:20

... pairs to A Shahina and B Yegnanarayana train a neural network model to capture the implicit mapping In the testing stage, the output of the trained network for each frame of the TM speech of a ... Signals, Macmillan, New York, NY, USA, 1993 [14] B Yegnanarayana, “On timing in time-frequency analysis of speech signals,” Sadhana, vol 21, part 1, pp 5–20, 1996 [15] A Shahina and B Yegnanarayana, ... [16] P Ladefoged, A Course in Phonetics, Harcourt College Publishers, Orlando, Fla, USA, 2001 [17] A Shahina and B Yegnanarayana, “Mapping neural networks for bandwidth extension of narrowband speech,”...

Ngày tải lên: 22/06/2014, 19:20

... Saratchandran, N Sundararajan, and K R Subramanian, A complex valued radial basis function network for equalization of fast time varying channels,” IEEE Transactions on Neural Networks, vol 10, no ... [23] A Uncini, L Vecci, P Campolucci, and F Piazza, “Complexvalued neural networks with adaptive spline activation function for digital-radio-links nonlinear equalization,” IEEE Trans Signal Processing, ... Bershad, P Celka, and J.-M Vesin, “Stochastic analysis of gradient adaptive identification of nonlinear systems with memory for Gaussian data and noisy input and output measurements,” IEEE Trans...

Ngày tải lên: 23/06/2014, 01:20

... Manage 2006;47(20):3659e71 289 [17] El Hamzaoui Y, Hernandez JA, Silva-Martinez S, Bassam A, Alvarez A, Lizama-Bahena C Optimal performance of COD removal during aqueous treatment of alazine and ... neural networks topology An artificial neural network is a system based on the operation of biological neural networks, a computational model inspired Fig e Relative impact (%) of input variables ... sawdust) for air and airesteam gasification In both ANNs models, the data sets containing the information (the values of input and output variables) of different biomass gasification tests are...

Ngày tải lên: 02/08/2016, 09:34

... mối quan hệ a = n

Ngày tải lên: 29/12/2013, 11:17

... boundary and the boundary variables are treated as P0 / -S primal events The unit models describe both normal and failed behavior and depend on a wide variety of operating parameters and failure ... is a failure such as S2 FO), then both of the NFFLs that pass along this path are inactivated In this case, the V3-V14 path will continue to propagate the disturbance and ultimately activate ... the causal relationships between variables including normal and failed states The basic elements of a digraph are shown in figure for conduction in a wire Node labels represent deviation variables,...

Ngày tải lên: 03/01/2014, 19:37