An Optimal Implementation on FPGA of a Hopfield Neural Network
Wassim Mansour, Rami Ayoubi, Haissam Ziade, Raoul Velazco, Wassim El Falou · Advances in Artificial Neural Systems · 2011
The associative Hopfield memory is a form of recurrent Artificial Neural Network (ANN) that can be used in applications such as pattern recognition, noise removal, information retrieval, and combinatorial optimization problems. This paper presents the implementation of the Hopfield Neural Network (HNN) parallel architecture on a SRAM‐based FPGA. The main advantage of the proposed implementation is its high performance and cost effectiveness: it requiresO(1) multiplications andO(log N) additions, whereas most others requireO(N) multiplications andO(N) additions.