The invention discloses a
convolutional neural network accelerator circuit based on a fast filtering
algorithm. In order to reduce the calculation amount of a
convolutional neural network algorithm (CNN), the method provided by the invention utilizes a fast filtering
algorithm to eliminate the redundancy of overlapped region calculation between convolutional windows in two-dimensional convolutionoperation, so that the algorithm strength is reduced, and the
convolution calculation efficiency is improved. Next, a
convolution calculation
acceleration unit of a four-parallel fast filtering algorithm is designed, and the unit is realized by adopting a parallel filtering structure which is composed of a plurality of small filters and is low in complexity. For the programmable
FPGA design, not only can the consumption of hardware resources be reduced, but also the running speed can be increased. Meanwhile, the
activation function is subjected to optimization design, and a hardware circuit ofthe
activation function (sigmoid) is designed by using a piecewise fitting method combining a
lookup table and a polynomial, so that the hardware circuit of the approximate
activation function is ensured not to reduce the precision.