Abstract
The main difficulties in neural network (NN) hardware implementations are the massive connections and problem oriented topology. It is proposed an efficient general purpose discrete-time multiplexing neuron array (MNA) to deal with these problems. A versatile precise multiplier is presented. The proposed MNA can configurate various neural topologies and the size of networks can be easily augmented. The implementations of Multi-Layer Perceptron (MLP), Fully-Connected Recurrent (FCR) and Bidirectional Associated Memory (BAM) are considered as applications of the MNA. The MNA can be applied to any type of discrete-time circuit implementation. The basic building blocks are implemented with multipliers and switched-capacitor integrators. Experimental IC building blocks results are in good agreement with theoretical results.
Original language | English |
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Pages (from-to) | 1320-1323 |
Number of pages | 4 |
Journal | Proceedings - IEEE International Symposium on Circuits and Systems |
Volume | 2 |
Publication status | Published - 1995 |
Event | Proceedings of the 1995 IEEE International Symposium on Circuits and Systems-ISCAS 95. Part 3 (of 3) - Seattle, WA, USA Duration: 1995 Apr 30 → 1995 May 3 |
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering