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An On-Chip Trainable and Scalable In-Memory ANN Architecture for AI/ML Applications
Traditional von Neumann architecture-based processors become inefficient in terms of energy and throughput as they involved separate processing and memory units, also known as memory walls. The memory wall pro...
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Article
Accuracy Enhancement of Epileptic Seizure Detection: A Deep Learning Approach with Hardware Realization of STFT
Electroencephalogram (EEG) signals, generated during the neuron firing, are an effective way of predicting such seizure and it is used widely in recent days for classifying and predicting seizure activity. But...
