Title :
Bridging the gap between molecular electronics and biocomputing
Author :
Akingbehin, Kiumi
Author_Institution :
Dept. of Electr. & Comput. Eng., Michigan Univ., Dearborn, MI, USA
Abstract :
Various biocomputing models for molecular electronic devices are examined. They are the feedforward connectionist network (artificial neural network), the enzymatic neuron, and a hybrid model that attempts to capture the programmability of silicon electronic devices and the adaptability of molecular electronic devices. Greater interaction between researchers in molecular electronics and in biocomputing is urged
Keywords :
biology computing; biomolecular electronics; neural nets; reviews; Si electronic devices; artificial neural network; biocomputing models; enzymatic neuron; feedforward connectionist network; hybrid model; molecular electronic devices; programmability; Application software; Artificial neural networks; Biological system modeling; Computers; Lattices; Materials science and technology; Molecular electronics; Neurons; Silicon; Transducers;
Conference_Titel :
Engineering in Medicine and Biology Society, 1989. Images of the Twenty-First Century., Proceedings of the Annual International Conference of the IEEE Engineering in
Conference_Location :
Seattle, WA
DOI :
10.1109/IEMBS.1989.96240
