Sentence examples for generalization training from inspiring English sources
However, it is known from studies in rehabilitation settings that in order to facilitate generalization, training locations and materials should bear as close a resemblance to the patients' experience and daily life as possible.
Psychoeducation, defining OCD as the identified problem, cognitive training, and development of a stimulus hierarchy (mapping OCD) took place during visits 1 4; EX/RP comprised visits 5 12, with the last two sessions incorporating generalization training and relapse prevention.
However, if it is assumed that during generalization training, the presentation of a stimulus activates the representation of the response, which becomes associated with the new response, then association-formation models can explain generalization on the basis of common consequences (Wills et al. 2006).
Stimulus generalization of training was measured by using photographs of trained items presented in natural contexts.
This generalization of training effect across stimulus type was also supported by the behavioral data, where a word-based training procedure influenced attention to pictures of faces.
These optimized operating data are then applied as target data for RBFNN generalization and training processes.
These optimized power data are then employed as target data for the RBFNN generalization and training process.
During this stage, the database extracted from the PSO process was used as a target data in the RBFNN/MLPNN generalization and training process.
To enable the online updating of the operating parameters, the proposed RBFNN is implemented in the management process, and the database extracted from the PSO process is used as target data in the RBFNN generalization and training.
In Experiment 1A, rats did not demonstrate rule-based generalization after training on one negative and one positive patterning problem.
Shanks and Darby (1998), building on earlier work by Lachnit and Kimmel (1993), tested generalization after training on negative and positive patterning problems in human predictive learning.
