2009 1st Asia Symposium on Quality Electronic Design 2009
DOI: 10.1109/asqed.2009.5206280
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Embedded Analog CMOS Neural Network inside high speed camera

Abstract: Analog VLSI on-chip learning Neural Networks represent a mature technology for a large number of applications involving industrial as well as consumer appliances. This is particularly the case when low power consumption, small size and/or very high speed are required. This approach exploits the computational features of Neural Networks, the implementation efficiency of analog VLSI circuits and the adaptation capabilities of the on-chip learning feedback schema. High-speed video cameras are powerful tools for i… Show more

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Cited by 5 publications
(5 citation statements)
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“…Inter-device variations change the performance of each ANN, resulting in unpredictable behavior and reduced accuracy. Some have attempted training each ANN individually to fine-tune the network so it learns to handle the unknown changes (i.e., on-chip training, chip-in-the-loop training), but this leads to a variety of costs in terms of manufacturing time, high-precision design, and non-transferrable, uninterpretable models [7], [11], [14]- [22]. The work covered in this paper is another step on the path to developing a train-once-programall method that achieves desirable levels of accuracy while minimizing inter-device performance variation.…”
Section: Living On the Edgementioning
confidence: 99%
“…Inter-device variations change the performance of each ANN, resulting in unpredictable behavior and reduced accuracy. Some have attempted training each ANN individually to fine-tune the network so it learns to handle the unknown changes (i.e., on-chip training, chip-in-the-loop training), but this leads to a variety of costs in terms of manufacturing time, high-precision design, and non-transferrable, uninterpretable models [7], [11], [14]- [22]. The work covered in this paper is another step on the path to developing a train-once-programall method that achieves desirable levels of accuracy while minimizing inter-device performance variation.…”
Section: Living On the Edgementioning
confidence: 99%
“…The Circuit neural network unit cell consists of (i)multipliers, (ii)OP-AMP, and (iii)sigmoid [1]. Multiplier circuit is used to do the calculations between input and weight given.…”
Section: A Multiplier Analog Neural Networkmentioning
confidence: 99%
“…This sigmoid function to generate activation functions for neurons. At the beginning of the design of neural networks that are based on a single architecture perceptron and Figure 1 as we proposed to redsign [1][2]. …”
Section: A Multiplier Analog Neural Networkmentioning
confidence: 99%
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