Study on Electro-polymerization Wiring System Imitating Axonal Growth of Artificial Neurons towards Machine Learning.

摘要

For years, brain emulation becomes academically interesting and important work. Since brain emulation is the logical endpoint of computational neuroscience attempts to accurately model neurons and brain systems. Machine learning using the artificial neuron network research is supposed to be the best way to understand how the human brain trains itself to process information. Derivation from the necessity of increasing in computation ability and in reduction of power consumption, accelerator circuits using on neural network training for machine learning become critical. Contrary to inorganic semiconductor based circuits, alternative circuits association with conducting polymer micro/nanowires must show advance features. Due to the unique characteristics, such as, conductive, flexible, predictable in wiring path, and selectable in polymerization direction, conducting polymer wires are the promising candidate for the project of optimization accelerator circuits.