This series of papers deal with vessels-target recognition. The project is conducted by using fuzzy neuraI networks and basing recognition on the spectra of vessel radiated-noise. Paper (Ⅰ) describes the characterist...This series of papers deal with vessels-target recognition. The project is conducted by using fuzzy neuraI networks and basing recognition on the spectra of vessel radiated-noise. Paper (Ⅰ) describes the characteristics of vessel radiated-noise spectra, which are composed of two distinctive categories: the stationary and the non-stationary. The project framework is introduced in the paper. It includes two steps. One is to extract effectively recognizable features (those common in one category and those distinguish categories). The other is to memorize the characteristics of specific vessel targets. The memorization is realized with characteristics pattern plate library of specific vessels (including line spectrum, double-frequency spectrum and average power spectrum pattern plate library). Detailed discussions on theories, models, parameter analysis, line-spectrum extraction methods, as well as gaps between reality and theory concerning vessels radiated-noise are also included in Paper (Ⅰ). Paper (Ⅰ) finally proposes a method of automatic extraction of line spectrum by using machines. Paper (Ⅱ) will discuss the stability, uniqueness of line spectrum and its pattern plate. Paper (Ⅲ) will focus on the extraction of features from double-frequency spectrum and average power spectrum, and the establishment of their pattern plates. Paper (Ⅳ) will discuss fuzzy neural networks and recognition approaches展开更多
文摘This series of papers deal with vessels-target recognition. The project is conducted by using fuzzy neuraI networks and basing recognition on the spectra of vessel radiated-noise. Paper (Ⅰ) describes the characteristics of vessel radiated-noise spectra, which are composed of two distinctive categories: the stationary and the non-stationary. The project framework is introduced in the paper. It includes two steps. One is to extract effectively recognizable features (those common in one category and those distinguish categories). The other is to memorize the characteristics of specific vessel targets. The memorization is realized with characteristics pattern plate library of specific vessels (including line spectrum, double-frequency spectrum and average power spectrum pattern plate library). Detailed discussions on theories, models, parameter analysis, line-spectrum extraction methods, as well as gaps between reality and theory concerning vessels radiated-noise are also included in Paper (Ⅰ). Paper (Ⅰ) finally proposes a method of automatic extraction of line spectrum by using machines. Paper (Ⅱ) will discuss the stability, uniqueness of line spectrum and its pattern plate. Paper (Ⅲ) will focus on the extraction of features from double-frequency spectrum and average power spectrum, and the establishment of their pattern plates. Paper (Ⅳ) will discuss fuzzy neural networks and recognition approaches
