Training mode

In the test of robustness to sensor drift it was shown that when the unsupervised part of the algorithm was allowed to run in on-line training mode drift robustness much superior to SVM and the new algorithm with no on-line learning was demonstrated. This is a promising result, but further characterization of this property is required. Additional evaluation is currently ongoing on a real chemosensor dataset. 

To set up the stimulation conditions described in Subheading 3.2.1. on a Grass S48 Stimulator (Grass Medical Instmments, Quincy, MA), the settings on the apparatus should be positioned as detailed in Table 2. Additionally it should be noted that train mode is set at repeat, pulses at single, and stimulation mode repeat at off. ... 

The Mode transition table can easily be modeled with CPN. The model corresponding to Table 1 is shown on Figure 4. The train mode is expressed as a token present in the corresponding place (NP, SB, OS, RV). The token is present in the initial state in NP place. In this case for example, if the condition 4 is fulfilled then the train can switch to SB mode. 

Now, you want to use your trained network to predict the dependent variable value for the 51st case—a pattern that is not in the training set and consists of a value for each of the five independent variables. Simply apply these five inputs to the input PEs and observe the output at the output PE. This is the predicted value. In this phase of operation the network is in a test mode or recall mode, as opposed to a training mode. 

FIGURE 19.26 A winner takes all architerture for cluster extracting in the unsupervised training mode (a) Network connections, (b) single-layer network arranged into a hexagonal shape. 

In training mode, the system can highlight hazards as the trainee navigates through the virtual workplace. 

The data addressing RMT for the main effects (phases, repetitions and training modes) were listed in Table 1. Analysis of variance demonstrated a significant difference among two modalities of exercise (p =. 00) and six phases of contraction ip =. 00). In addition, interaction of the main effects exhibited statistically significant values for phases x training mode ip =. 044), and phases x repetitions x training... 

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