DocumentCode :
2699788
Title :
GaAs/AlGaAs based multiquantum well device for learning and decision making in optical neuro-computers
Author :
Goswami, S. ; Biswas, D. ; Bhattacharya, P.K. ; Singh, J.
fYear :
1990
fDate :
17-21 June 1990
Firstpage :
795
Abstract :
Theoretical and experimental examinations are made of two classes of devices which have the requisite properties for learning and neuronlike decision making. These properties involve responding to a time sequence of optical pulses (for learning) and integrating the thresholding and are realized in GaAs/AlGaAs multiquantum wells (MQWs) using the quantum confined Stark effect. The device is compatible with heterojunction bipolar transistor (HBT) technology since the controller is simply an HBT structure with a built-in MQW structure. Therefore, it should be possible to make use of the advances in HBT technology and develop large neuron arrays. Also, due to the current gain in the controller-modulator (C-M) device, the optical power requirements (~10 μW per device) are consistent with semiconductor laser structures, and one does not require high-power lasers. Based on the estimation of optical power dissipation (⩽10 W/cm2) with current technology it should be possible to achieve a 1000-b array with each C-M device being about 20 μm in diameter
Keywords :
III-V semiconductors; aluminium compounds; electro-optical devices; gallium arsenide; integrated optoelectronics; learning systems; neural nets; optical information processing; semiconductor quantum wells; GaAs-AlGaAs; MQW; decision making; learning; multiquantum well device; optical neuro-computers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1990., 1990 IJCNN International Joint Conference on
Conference_Location :
San Diego, CA, USA
Type :
conf
DOI :
10.1109/IJCNN.1990.137959
Filename :
5726916
Link To Document :
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