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ABSTRACT
<p>Developed for the VLSI implementation of neural network models, our novel analog architecture adds flexibility and adaptability by incorporating digital processing capabilities. Its systolic-based architecture avoids static storage of analog values by transferring the activation values through the chip's processing units. This proposed combination of analog and digital technologies produces a densely packed, high-speed, scalable architecture, designed to easily accommodate learning capabilities.</p>
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CITATION
Jordi Madrenas, Francisco Castillo, Andrezj Napieralski, Joan Cabestany, Juan M. Moreno, "An Analog Systolic Neural Processing Architecture", IEEE Micro, vol. 14, no. , pp. 51-59, June 1994, doi:10.1109/40.285224
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