A Shannon Based Low Power Adder Cell for Neural Network Training

The proposed full adders for low power and high performance neural network training circuits has been implemented using Shannon decomposition based technique for sum and carry operation. The hardware includes multiplier circuit for product term and an adder circuit to perform summation. The proposed full adder is designed using tanner EDA tools and the resulting parameters such as 25.6% improvement in power dissipation and 20% improvement in transistor count from the simulated output when compared with MC IT based adder cell.

Provided by: International Association of Computer Science and Information Technology(IACSIT) Topic: Hardware Date Added: Jun 2010 Format: PDF

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