Impact of Program Accuracy and Random Telegraph Noise on the Performance of a NOR Flash-based Neuromorphic Classifier.
Gerardo MalavenaSimone PetròAlessandro S. SpinelliChristian Monzio CompagnoniPublished in: ESSDERC (2019)
Keyphrases
- feature selection
- noisy data
- highest accuracy
- high accuracy
- noise immunity
- classification algorithm
- training data
- error rate
- training samples
- individual classifiers
- noise level
- classification rate
- fold cross validation
- feature space
- support vector
- multiple classifier systems
- random selection
- support vector machine classifier
- figure of merit
- roc curve
- improve the recognition accuracy
- classification accuracy
- learning algorithm
- decision trees
- high classification accuracy
- data sets
- neural network
- bias variance
- low light
- machine learning
- noise sensitivity
- higher classification accuracy
- noise reduction
- computational cost
- measurement error
- multi class
- classifier combination
- recognition rate
- computer programs
- input data