ABSTRACT
Neurodegenerative illnesses are global epidemics that disrupt the lives of millions of people in every part of the world. These disorders are known as neurodegenerative diseases. There is currently no medicine that has been proved to be capable the progression of the disease itself. In this paper, we develop a cognitive based learning in Feed forward MLP (Multi- Layer Perceptron) for classification of neurodegenerative disorders. The dataset is split into training and test data, where the FFMLP model is trained using the pre-processed datasets. Then the trained MLP model is tested using the test dataset and finally the classified instances are depicted. The simulation is conducted to test the efficacy of the FFMLP model over various input images. The results of simulation show that the proposed method achieves higher accuracy, precision, recall and f-measure than existing methods.
