Optimization of neural-network-based superdirective microphone-array system using a genetic algorithm

抄録

A previous study indicated that superdirectivity is achieved with a microphone-array system consisting of seven microphones and a neural network. In this work, we aim to improve the directivity by optimizing the parameters of the neural network using a genetic algorithm. A computational simulation shows that the optimized system can produce superdirectivity with a half-width of five degrees. The optimized system improves the directivity because its side-lobes are suppressed by more than 10 dB compared with the results of the previous study. This suppression is also observed in terms of harmonic distortions. Moreover, in an examination using AM and FM waves as input signals, the optimized system achieves higher performances than those in the previous study.