Abstract: The neuro-fuzzy classifier of seabed type from acoustic echoes was investigated in the context of possible reducing the number of input parameters. The incremental architecture of fuzzy neural network classifier (IFNN) was used in the experiment, utilising dual-frequency echo collection. In particular, the wavelet decomposition of these bottom echoes was used to generate input parameters of IFNN. The Principal Component Analysis (PCA) was subsequently applied for redundant parameters reduction.