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Characteristic Acquiring and Analyzing of Underwater Transient Signal
Author: LvChengGang
Tutor: LiSiChun
School: Harbin Engineering University
Course: Underwater Acoustics
Keywords: Empty invested in water HHT Feature Extraction FARTMAP Target classification
CLC: TN911.6
Type: Master's thesis
Year: 2009
Downloads: 183
Quote: 3
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Abstract
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Torpedo the empty inputs such as water, underwater transient signals into the water target classification , for the torpedo early warning has important significance . Extremely complex underwater background noise , as well as transient signal generation involves a very complex set of factors , the field has become a difficult and hot water sound research . The focus of this paper is to analyze and classify research into the water target object empty into the characteristics of the underwater acoustic torpedoes . This paper describes the torpedo objects such as empty physical processes put into water , and analyzed signal composed into the water - splashing into the water pulse signal and vacuolar volume pulsation signal and its characteristics . Into the water signal is a non- stationary signals , so the main theory suitable for the analysis of non- stationary signals - the Hilbert - Huang transform ( Hilbert 's - Huang, Transform referred HHT) to handle HHT theory in the frequency domain and time domain can also get many of the advantages of the high-resolution . This paper analyzes the connotation of the theory of HHT and its simulation study , the text in the theory and the Wavelet Transform contrast , HHT handle null input the water transient signals smaller wavelet transform has certain advantages . According to the characteristics of the water signal , splashing into the water pulse signal detection is of great significance for the early discovery of the aerial torpedo This article studies the energy method , higher-order statistics splashing into the performance of the pulse signal detection : HHT theory applied to the vacuolar volume pulsation signal the vacuolar volume pulsating signal processing the Hilbert spectral characteristics , anechoic water tank the experimental and Songhuahu experiment experimental data processing . Fuzzy adaptive resonance mapping (Fuzzy Adaptive Resonance Theory Mapping, the referred FARTMAP) neural network is the network stability and plasticity . At the end of this article described its principles and neural network structure and its simulation study , while the neural network introduce air into the water target classification study it handled Songhuahu experimental data to study the different parameters put into water -to-air target classification problem .
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