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 SVM, 4 classes (6, 7, 8, nonfixation) Jian and Tang  OVO RBF SVM, 5 classes (8,10,12,14,15 Hz) Cecotti and Graser  TDNN, 5 classes (13,14,15,16,17 Hz) Cecotti  CNN, 5 classes (6.66, 7.5, 8.57,10,12 Hz) Hartmann and Kluge  HMM, 3 classes (10, 12, 15 Hz) Ko et al.
In this study, the following 28 ANNs were built and compared using the NeuroSolution for Excel 6.3 software (Neuro Dimension Inc.): six MLP, three MLP with principal component analysis (MLPPCA), three generalized feedforward (GFF), three RBF, three TDNN, three time-lag recurrent network (TLRN), three RN, two linear regression (LR), one probabilistic neural network (PNN) and one SVM models (Table 1).
Hence, our suggested CMESI implements knowledge manipulation using TDNN.
Robot implemented using TDNN based on our theoretical cognitive model could predict opponents next behavior on the basis of its current observations and past experiences.
Among them are: time-delay neural networks (TDNN), Nearest Neighbor Method (NNM), Nearest Neighbor (Correlation), Nearest Neighbor (Absolute Distance) and ARMA (Auto Regressive Moving Average) Models.
Chan, "Prediction of hourly solar radiation using a novel hybrid model of ARMA and TDNN," Solar Energy, vol.
Based on the necessary aspects that we must consider in recognizing gestures we present a method for gesture recognition using Time Delay Neural Networks (TDNN) .
The information provided by Kinect is processed and we obtain the relevant data which will be used to train the TDNN. After the training phase we test the learned model and determine the error rate.
* the training module--trains the TDNN; the input data is composed by the feature vectors computes by the processing module; The parameters of the trained TDNN are saved in the TDNN Parametres database.
d) Time-delay neural network (TDNN): TDNN is also an interesting approach to analyzing time-varying data.
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- TDMS -Trex mammography
- TDN DDS-M