基于神经网络并行算法的海尔伯特变换器优化设计

Optimal Design Study of Hilbert Convertor Based on Parallel Algorithm of Neural Networks

研究了一种基于神经网络并行算法的海尔伯特变换器优化设计方法,提出并证明了神经网络算法的收敛性定理,给出了海尔伯特变换器优化设计实例.仿真结果表明用该算法设计的海尔伯特变换器具有高的计算精度和快的收敛速度,因而是有效的.

Traversed an optimal design method on Hilbert convertor based on neural network parallel algorithm, the converggence theorem of neural network parallel algorithm is presented and proved, and given the optimal design examples of high order Hilbert convertor. The results show that neural network parallel algorithm presented has a high accuracy and fast convergence speed in the field of optimal design of Hilbert convertors. Therefore, the algorighm introduced is effective.