Optimization of neural network with fixed-point number weights and its application
一种定点数权值神经网络的优化方法及其应用

In order to make the neural network application suffice the demands of double-quick computing and tidy memory capacitance in embedded systems, an optimization method of neural network with fixed-point number was proposed. The neural network weights were represented with the precision-adjustable fixed-point number and the neural network was trained by using the genetic algorithm. And the continuous nonlinear activation function of the neuron was transformed into discrete and linear function by the least-squares algortithm. Then, the optimal neural network was applied to a touch-screen-LCD adjusting model for verifying its feasibility. Experiments show that this touch-screen-LCD calibration method has higher accuracy compared with the traditional one.