Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes a novel evolutionary approach to the optimal selection of electrodes as ll as relevant EEG features for effective classification of cognitive tasks. The problem has been formulated in the framework of a single objective optimization problem with an aim to simultaneously satisfy three criteria. The first criterion deals with maximization of the correlation beten the features of EEG sources before and after the selection of the optimal electrodes. The second criterion is concerned with minimization of the mutual information beten the features of the selected EEG electrodes. The last criterion aims at maximization of the ratio of the difference beten the selected features of the EEG sources beten and within any two cognitive tasks. A self-adaptive variant of firefly algorithm is proposed to solve the above optimization problem by proficiently balancing the trade-off beten the computational accuracy and the run-time complexity. Experiments undertaken over wide variety of cognitive tasks reveal that the proposed algorithm outperforms the other standard algorithms (applied to the same problem) in terms of accuracy and computational overhead.
['Rimita Lahiri', 'Pratyusha Rakshit', 'Amit Konar', 'Atulya K. Nagar']
I am writing a research paper on a idea Evolutionary approach for selection of optimal EEG electrode positions and features for classification of cognitive tasks
[{"from": "human", "value": "I am writing a research paper on a idea Evolutionary approach for selection of optimal EEG electrode positions and features for classification of cognitive tasks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes a novel evolutionary approach to the optimal selection of electrodes as ll as relevant EEG features for effective classification of cognitive tasks. The problem has been formulated in the framework of a single objective optimization problem with an aim to simultaneously satisfy three criteria. The first criterion deals with maximization of the correlation beten the features of EEG sources before and after the selection of the optimal electrodes. The second criterion is concerned with minimization of the mutual information beten the features of the selected EEG electrodes. The last criterion aims at maximization of the ratio of the difference beten the selected features of the EEG sources beten and within any two cognitive tasks. A self-adaptive variant of firefly algorithm is proposed to solve the above optimization problem by proficiently balancing the trade-off beten the computational accuracy and the run-time complexity. Experiments undertaken over wide variety of cognitive tasks reveal that the proposed algorithm outperforms the other standard algorithms (applied to the same problem) in terms of accuracy and computational overhead."}]