Bridging the gap between molecular electronics and biocomputing

Author

Akingbehin, Kiumi

Author_Institution

Dept. of Electr. & Comput. Eng., Michigan Univ., Dearborn, MI, USA

fYear

1989

fDate

9-12 Nov 1989

Firstpage

1360

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/IEMBS.1989.96240

Filename

96240

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1829036