Skip to Main Content
This paper presents a preprocessing for neural computing using the quaternion Fourier transform. The 1D signals of French vocables are represented as 2D signals in the frequency and time domain. The images are convolved in the quaternion Fourier domain with a quaternion Gabor filter for the extraction of features. Two methods of feature extraction are tested. The features vectors are then used for the training of two neural network architectures. The results are very encouraging which justify plenty the preprocessing in the quaternion frequency domain.